JPH10207455A - Sound signal analyzing device and its method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable analyzing a musical steady part other than a fluctuated part, that is, a part corresponding to one notation even if a pitch or a level of an input sound from a microphone and the like are fluctuated delicately, by making a device such constitution that a second section for analyzing a sound signal is detected by section analysis of two stages. SOLUTION: This device is controlled by a microcomputer consisting of a CPU 1, a program memory 2, and a working memory 3. And in this device, an average value including the prescribed number of samples with each sample amplitude value of a sound signal inputted from an input means is obtained. Therefore, average level information varying smoothly responding to level variation of an inputted sound signal can be obtained, a section assumed that a musical sound exists, that is, an effective section can be appropriately detected as a first section. And a section suitable for analyzing a sound signal can be appropriately detected by making this effective first section as an object and detecting a second section from it.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a section (effective section) in which a musical sound exists based on a sound signal whose pitch or note is undetermined, such as an audio signal or a tone signal input by a microphone or the like. The present invention relates to a sound signal analyzing apparatus and method capable of analyzing a stationary portion of the musical sound and automatically analyzing the note (note name of the scale) and the note length, and further stores a program therefor. Related to a recorded medium. The analysis result according to the present invention can be output as electronic musical score information in the form of MIDI information or the like as necessary. Therefore, the present invention automatically converts audible melody input by human voice or the like. The present invention relates to a technology that can be converted into a score.

[0002]

2. Description of the Related Art Recently, MIDs have been
A computer performance system that generates performance information such as I information and reproduces performance sounds based on the performance information has attracted attention as a new musical performance apparatus. In this type of computer performance system, a method for inputting data for generating performance information includes a real-time input method, a step input method, a numerical value input method, a score input method, and the like. The real-time input method is a method of converting operation information of a performance operator such as a keyboard actually played by a player like a tape recorder into performance information in real time. The numerical value input method is a method in which performance information such as a pitch (pitch), a sound length, and the strength of a sound is directly input as numerical data from a computer keyboard. The score input method is a method in which simplified music symbols and the like are arranged in a score (5-line notation) on a display using a function key of a computer, a mouse, or the like. The step input method uses MIDI
In this method, the sound is input using a keyboard or a software keyboard, and the sound length is input using a function key of a computer, a mouse, or the like.

[0003] Among the above-mentioned input methods, the real-time input method can store the actual performance operation state as performance information as it is, so that it is easy to express subtle human nuances in the performance, and it is also easy to express in a short time. It has the advantage that input is possible. However, this method requires the player to have a high level of musical instrument playing ability, and is not suitable for beginners. Therefore, as a performance information generator that allows beginners to easily input performance information in a short time by taking advantage of the real-time input method, a human voice or a musical instrument of a natural instrument is directly input via a microphone, and the input sound is input. In some cases, performance information is generated in response to a request. That is,
In this method, a MIDI signal can be easily generated only by inputting a human voice or a sound (single sound) of a guitar or the like from a microphone, and a MIDI device can be controlled without using a MIDI keyboard or the like.

[0004]

In a conventional performance information generating apparatus, MIDI information is generated by performing the following processing for a pitch change of a sound input from a microphone. That is, the first method detects a pitch change in semitone units,
Only note information of the pitch is generated. The second method detects a pitch change in semitone units, and generates note information of the pitch and pitch bend information (pitch change information) relating to a pitch change therebetween. The third method is to generate pitch bend information that can change the pitch of an input signal in the range of one octave up and down without detecting a note.
To generate note information (note on or note off), the level of the input sound is compared with a predetermined reference value, and when the level of the input sound becomes higher than the reference value, the note-on is reduced. A note-off has occurred at that point. However, in the case where the pitch change is detected in semitone units as in the first and second methods, if the pitch of the input sound is slightly changed, a lot of unintended note information (note on or note off) is generated. There is. Further, when the pitch change is generated by the pitch bend information as in the third method, the pitch change can be accurately followed by the pitch bend information, but is not suitable for purposes such as transcription. Further, when note information is generated according to the input level, there is a problem that a large number of unintended note information is generated according to the fluctuation of the level of the input sound.

In the real-time input method, since a plurality of sounds are input to the microphone in a time series at arbitrary time intervals, it is required to efficiently analyze a portion where the sound exists. . That is, it is not preferable that the analysis of the pitch and the like is constantly performed on the signal input to the microphone, because useless analysis processing is performed even during the time when no sound is actually input.
Therefore, it is efficient to extract a section (effective section) where a sound actually exists from a signal input to the microphone, and to perform a complicated analysis process such as pitch analysis only on the extracted effective section. is there. In the conventional method for extracting an effective section, the effective section is simply extracted by comparing a predetermined reference level with an input signal level. If it fluctuates in the vicinity, there is a problem that the extraction of the effective section becomes inaccurate.

According to the present invention, even when the pitch or level of an input sound from a microphone or the like is slightly fluctuated, a stationary part of a musical sound other than the fluctuated part, that is, a part corresponding to one note, is analyzed. It is an object of the present invention to provide a sound signal analyzing device and a sound signal analyzing method. More specifically, a stationary part is effectively analyzed from an input sound signal, and a pitch of a sound can be accurately analyzed based on the effective part.
This analysis result can be output as electronic musical score information in the form of MIDI information or the like, if necessary, so that audible melody input by human voice or actual musical instrument performance can be automatically output. It is an object of the present invention to provide a technique capable of accurately performing musical score conversion.

[0007]

According to a first aspect of the present invention, there is provided a sound signal analyzing apparatus, comprising: input means for inputting an arbitrary sound signal; and a sound signal input from the input means. Calculating means for calculating an average value of the sample amplitude values over a predetermined number of samples, and outputting the result as time-series average level information; and First section detecting means for detecting a first section in which a musical sound is considered to exist, and a second section for sound signal analysis based on a sample amplitude value of the sound signal in the first section. Is detected from the first section by a second section detecting means. Since the average value of each sample amplitude value of the sound signal input from the input means over a predetermined number of samples is obtained, it is possible to obtain the average level information that smoothly changes in response to the level fluctuation of the input sound signal. Thus, a section where a musical sound is considered to exist, that is, an effective section can be appropriately detected as the first section. Since the second section is further detected from the effective first section, a section suitable for sound signal analysis is appropriately detected as the second section. be able to. Since the second section for sound signal analysis is detected by such two-step section analysis, a section suitable for sound signal analysis, for example, a stable section suitable for pitch detection can be appropriately detected. And the accuracy of sound analysis, especially pitch detection, can be improved. Note that such a second section is one first section.
Is not limited to one, and a plurality of sections may exist.

[0008] In one embodiment of the sound signal analyzer according to the first aspect, the second section detecting means determines a section in which the inclination degree of the average level information is equal to or less than a predetermined value, and determines the section of the determined section. A portion having a length equal to or longer than a predetermined length is determined as a level stable section, and the second level is determined based on the level stable section.
May be detected. The smaller the gradient level of the average level information, the smaller the fluctuation of the amplitude level of the sound signal, that is, it means that it is stable. Need to be. In other words, even if the gradient frequency of the average level information is equal to or less than a predetermined value, if the section length is short, it cannot be said that the section is a stable section, so that it is excluded. Therefore, it is appropriate to determine a portion in which the temporal length of the section in which the inclination frequency is equal to or less than the predetermined value is equal to or more than the predetermined length as the level stable section.

A sound signal analyzing apparatus according to the present invention according to claim 2 of the present application is an input means for inputting an arbitrary sound signal, and a predetermined sample amplitude value of the sound signal input from the input means. A waveform generating unit that detects the maximum value for each number of samples and creates an auxiliary waveform by interpolating the detected maximum value; and from the sound signal based on the auxiliary waveform created by the waveform creating unit. A first section detecting means for detecting a first section in which a musical sound is considered to exist; and a second section for sound signal analysis based on a sample amplitude value of the sound signal in the first section. , The first
And a second section detecting means for detecting from among the sections. In this case, in order to detect the first and second sections similar to the above, an interpolated waveform created by the waveform creating means is used. For example, this interpolated waveform is obtained as a waveform similar to an amplitude envelope waveform connecting between peak levels of the sound signal waveform, and indicates a tendency of the amplitude level of the sound signal. Since the calculation of such an interpolated waveform can be performed more quickly than the calculation of the average level information, the processing speed can be increased, the detection speed of each section can be improved, the analysis time of the sound signal can be reduced, In addition, the load on the arithmetic unit for that purpose can be reduced.

In one embodiment of the sound signal analyzing apparatus according to the second aspect, the second section detecting means detects a maximum value by performing envelope detection on the sample amplitude value of the sound signal from both directions. Then, a maximum value interpolation curve is obtained by interpolating the detected maximum value, and a total slope at each sample point is obtained based on the obtained maximum value interpolation curve. A determination may be made as a level stable section, and the second section may be detected based on this level stable section. In this manner, by performing envelope detection from both, it is possible to prevent a harmonic peak from being erroneously detected as a pitch peak in a waveform whose level gradually increases.

The sound signal analyzer according to the present invention according to claim 3 of the present invention is an input means for inputting an arbitrary sound signal, and a filter means for performing a filtering process of a predetermined frequency characteristic on the sound signal. Analyzing means for analyzing the degree of coincidence between adjacent waveforms based on successive sample amplitude values in the sound signal after the filtering, and analyzing that the analysis means matches within a range according to a predetermined condition. And a pitch detecting means for detecting a pitch of the sound signal in the same waveform section detected by the section detecting means. It is. By appropriately shaping the waveform of the input sound signal by filter processing of a predetermined frequency characteristic, the analysis processing of the degree of coincidence of the waveform by the analysis means can be facilitated and accurate. The same waveform section detected by the section detecting means is a section in which a plurality of waveforms that can be regarded as substantially the same waveform are continuous, and is a section in which the waveform shape is stable. Therefore, in such a waveform section, the pitch of the input sound signal is also stable, and is suitable for the target section of the pitch detection processing. Therefore, appropriate pitch detection of the input sound signal can be accurately and easily performed. It can be carried out. Further, pitch detection / analysis processing of an input sound signal based on the same waveform section is performed in such a manner that a note delimiter cannot be found from fluctuations in the amplitude level. This is extremely useful when a chunk as a note is distinguished from, for example, a slur effect sound with a changing waveform, and the pitch is analyzed.

The sound signal analyzing apparatus according to the present invention according to claim 4 of the present application is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided at every predetermined interval. First pitch detecting means for respectively detecting the pitch of the sound signal and generating a data string of the detected pitch, and filtering processing in which a pass band is variably controlled according to a frequency corresponding to each pitch in the pitch data string. , Filtering means for applying to the input sound signal,
Second pitch detecting means for detecting a more accurate pitch of the sound signal based on a sample amplitude value of the sound signal output from the filtering means. The pitch detection by the first pitch detection means may correspond to the approximate pitch of the input sound signal, and performs a rough waveform period measurement of the input sound signal, and generates a pitch data sequence based on the time series. Get to. The filter processing means performs a time-varying filter process on the input sound signal when the pass band is variably controlled according to the frequency corresponding to each pitch in the pitch data sequence. Thereby, the waveform of the input sound signal can be shaped as close to a sine wave as possible so that the fundamental wave component of the sound signal can be extracted as much as possible according to the instantaneous pitch. The pitch detection processing by the target second pitch detection means can be easily and accurately performed.

The sound signal analyzing apparatus according to the present invention according to claim 5 at the time of filing is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided for each predetermined section. First pitch detecting means for respectively detecting the pitch of the sound signal and generating a data string of the detected pitch, and filtering processing in which a pass band is variably controlled according to a frequency corresponding to each pitch in the pitch data string. , Filtering means for applying to the input sound signal,
Analyzing means for analyzing the degree of coincidence between adjacent waveforms based on continuous sample amplitude values in the filtered sound signal; and analyzing means that the adjacent waveforms are matched within a range according to a predetermined condition. A section detecting means for detecting a section including a plurality of continuous waveforms as the same waveform section; and a second pitch detecting means for detecting a pitch of the sound signal in the same waveform section detected by the section detecting means. Things. Similarly to the above, the first pitch detection means and the filter processing means perform time-varying filter processing on the sound signal in accordance with the pitch tendency of the input sound signal, whereby the fundamental The waveform can be shaped to be as close to a sine wave as possible so that the waveform component is extracted. Therefore, the processing of detecting the same waveform section by the analyzing means and the section detecting means for the filtered sound signal waveform can be easily and accurately performed, and the second processing for the same waveform section can be performed. Pitch detection processing by the pitch detection means can be easily and accurately performed.

The sound signal analyzer according to the present invention according to claim 6 at the time of filing is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided at predetermined intervals with respect to the sound signal. First pitch detection means for respectively detecting the pitch of the sound signal and generating a data string of the detected pitch, and filtering processing in which a pass band is time-varying controlled according to a frequency corresponding to each pitch in the pitch data string Filter processing means for applying to the input sound signal,
Analyzing means for analyzing the degree of coincidence between adjacent waveforms based on continuous sample amplitude values in the filtered sound signal; and analyzing means that the adjacent waveforms are matched within a range according to a predetermined condition. First section detection means for detecting a first section consisting of a plurality of continuous waveforms;
Based on the waveform having a higher degree of coincidence in the first section detected by the first section detecting means, the degree of coincidence is determined between a plurality of waveforms before and after the waveform, and a second section having a higher degree of coincidence is determined. And a second pitch detecting means for detecting a pitch of the sound signal in the second section detected by the second section detecting means. Similarly to the above, the first pitch detection means and the filter processing means perform time-varying filter processing on the sound signal in accordance with the pitch tendency of the input sound signal, whereby the fundamental The waveform can be shaped to be as close to a sine wave as possible so that the waveform component is extracted. Therefore, a first section by the analyzing means and the first section detecting means for the filtered sound signal waveform, that is, a section having a relatively high degree of waveform matching,
Can be easily and accurately performed. Further, the second section detection means determines the degree of coincidence between a plurality of waveforms before and after the waveform having a higher degree of coincidence in the first section detected by the first section detection means. , A second section having a higher degree of coincidence is detected, and the second pitch detection means performs the pitch detection processing on the second section, so that a more stable section is extracted as the second section. By performing pitch detection on the section, pitch detection processing can be performed more easily and accurately.

In one embodiment of the sound signal analyzer according to any one of claims 4 to 6, the first pitch detection means includes a temporary reference which is a period reference for the sound signal input by the input means. Provisional period reference detecting means for detecting a plurality of candidate positions; and a pitch for detecting a pitch of the sound signal for each of the provisional candidate positions based on the detected provisional candidate positions and generating a data sequence of the detected pitch. Data sequence generating means, and the provisional period reference detecting means detects a peak position by focusing on one of the waveforms on the plus side or the minus side of the amplitude of the sound signal, where a strong peak appears. , The peak position may be detected as a provisional period reference. By such a pitch detection (provisional period measurement) for each provisional candidate position, a rough waveform period measurement of the input sound signal can be performed, and a pitch data sequence based on the measurement can be easily obtained in time series. It is advantageous. Also, the peak position is detected by focusing on one of the waveforms on the plus side or the minus side of the amplitude of the input sound signal where a strong peak appears, and the peak position is detected as a provisional period reference. Even if the amplitude of the sound signal has a bias in the positive / negative level, that is, if the swing of the sound signal appears strongly on either the plus side or the minus side of the amplitude, the appropriate Tentative period detection can be performed.

In one embodiment of the sound signal analyzing device according to any one of claims 4 to 6, the first pitch detecting means includes a temporary reference which is a period reference for the sound signal input by the input means. Provisional period reference detecting means for detecting a plurality of candidate positions; and a pitch for detecting a pitch of the sound signal for each of the provisional candidate positions based on the detected provisional candidate positions and generating a data sequence of the detected pitch. And a data string generating means, wherein the pitch data string generating means generates the pitch data string by interpolating pitch data of the sound signal obtained for each of the tentative candidate positions. May be. Again,
By such a pitch detection (provisional period measurement) for each provisional candidate position, a rough waveform period measurement of the input sound signal can be performed, and a pitch data sequence based on the measurement can be easily obtained in time series. It is advantageous. Further, the pitch data string generating means generates a finer pitch data string by interpolating the pitch data of the sound signal obtained for each of the tentative candidate positions.
Filter processing that fluctuates more finely between the temporary candidate position and the temporary candidate position can be performed, and the analysis accuracy can be improved.

In one embodiment of the sound signal analyzing device according to the fifth or sixth aspect, the analyzing means detects a plurality of candidate positions as a cycle reference for the filtered sound signal. Detecting means for determining a degree of coincidence of waveforms between adjacent sections for a plurality of sections of the sound signal divided corresponding to the plurality of detected candidate positions; The detecting means detects the peak position by focusing on one of the waveforms on which the peak appears strongly on the plus side or the minus side of the amplitude of the sound signal, and detects the peak position on a cycle basis. It may be. Thus, the analysis means can perform waveform comparison between sections divided for each candidate position corresponding to the waveform period, and thus can easily and accurately determine the degree of waveform coincidence. Is advantageous. In addition, the peak position is detected by focusing on one of the waveforms where a strong peak appears on the plus side or the minus side of the amplitude of the sound signal. Even if the amplitude of the signal has a bias in the positive or negative level, that is, if the sound signal swings strongly on either the plus side or the minus side of the amplitude, an appropriate period Detection can be performed.

In one embodiment of the sound signal analyzing apparatus according to the fifth or sixth aspect, the analyzing means detects a plurality of candidate positions serving as a cycle reference for the filtered sound signal. Detecting means for determining a degree of coincidence of waveforms between adjacent sections for a plurality of sections of the sound signal divided corresponding to the plurality of detected candidate positions; The detection means focuses on one of the waveforms on the plus side or the minus side of the amplitude of the sound signal waveform after the time-varying filter processing performed by the filter processing means, and is used for the time-varying filter processing. The sound signal waveform is divided at a cycle corresponding to a cutoff frequency, and a peak position that is maximum in the divided section is detected as a cycle reference. Good me. Also in this case, the analysis means can perform the waveform comparison between the sections divided for each candidate position corresponding to the waveform cycle, so that the processing of determining the degree of waveform coincidence can be easily and accurately performed. So it is advantageous. Also, focusing on one of the waveforms on the plus side or the minus side of the amplitude of the sound signal waveform after the time-varying filter processing performed by the filter processing means, the cutoff used in the time-varying filter processing. The sound signal waveform is divided by the frequency cycle, and the peak position that is maximum in the divided section is detected as a cycle reference. This eliminates the possibility of erroneously detecting a peak that occurs in a cycle, thereby improving the detection accuracy of the peak position and consequently improving the analysis accuracy of the sound signal.

In one embodiment of the sound signal analyzer according to any one of claims 4 to 6, a section in which the state of the signal is stable is detected from the sound signal input from the input means. Further comprising a stable section detecting means;
The pitch detecting means may detect a pitch with respect to the sound signal in the stable section detected by the stable section detecting means. As described above, by detecting the stable section from the input sound signal and performing the pitch detection processing by the first pitch detection section on the stable section, the pitch detection processing by the first pitch detection section can be quickly performed. As a result, the analysis processing of the sound signal can be performed at high speed and accurately as a whole.

In one embodiment of the sound signal analyzing apparatus according to the sixth aspect, the second section detecting means has the highest degree of coincidence detected by the first section detecting means within the first section. A comparison error is sequentially calculated between a plurality of waveforms before and after the waveform based on the waveform, and a portion including a plurality of continuous waveforms in which the comparison error is equal to or less than a predetermined value is detected as a timbre section, and the first section is performed. If the length of the remaining portion other than the timbre section is equal to or longer than a predetermined length, the timbre section is similarly detected for the remaining portion, and the remaining The timbre section may be detected until the length of the portion of the first section becomes equal to or less than a predetermined length, and one or more detected timbre sections may be set as the second section. When there are a plurality of timbre sections in the first section, and when the length of the remaining first section other than the first detected timbre section is a predetermined length or more, the remaining first section Assuming that another timbre section exists in the
By detecting all the detected tone color sections as the second sections having a stable waveform shape, accurate detection can be performed.

The sound signal analyzer according to the present invention described in claim 7 at the time of filing is an input means for inputting an arbitrary sound signal, and a band pass having a predetermined cutoff frequency as a maximum frequency and a minimum frequency. First filter processing means for performing filter processing on the sound signal input from the input means, and detecting a plurality of first candidate positions serving as a period reference for the sound signal output from the first filter processing means First
Frequency band detection means for detecting a maximum frequency and a minimum frequency of the sound signal based on the cycle reference detection means and the first candidate position detected by the first cycle reference detection means; A second filter processing unit that performs band filter processing using the maximum frequency and the minimum frequency as a cutoff frequency on the sound signal input from the input unit, and the sound signal output from the second filter processing unit. A second cycle reference detecting means for detecting a plurality of candidate positions serving as a cycle reference, and a pitch detecting means for respectively detecting a pitch of the sound signal for each of the candidate positions detected by the second cycle reference detecting means. It is equipped. According to this, since the period candidate position is detected after performing the filtering process twice, accurate pitch detection can be performed.

A sound signal analyzing apparatus according to the present invention according to claim 8 of the present application is an input means for inputting an arbitrary sound signal, and a filter means for performing a filtering process of a predetermined frequency band on the sound signal. A peak position detecting means for respectively detecting a peak position of the sound signal after the filtering processing by the filter means; and a waveform of the sound signal is divided between any two peak positions detected by the peak position detecting means. Of the various sections obtained in this way, for a section having a time length commensurate with the restriction by the pass band of the filter, a pair of adjacent two sections is selected as many as possible, and two sections in each selected pair are selected. A section detecting means for judging the degree of coincidence of the waveforms and detecting one pair having the highest degree of coincidence as the same waveform section; The in which it equipped with a constant interval detection means for detecting the constant section for the sound signal analysis based on the waveform segment. The peak positions of the waveform in the sound signal appear in various ways, and the interval between adjacent peak positions does not always correspond to the waveform period. Therefore, it is necessary to appropriately determine which peak position pair corresponds to the waveform period by the section detecting means. Therefore, by passing the sound signal through a filter, a pair of peak positions at a time interval longer than a period corresponding to the pass band can be excluded from candidates of a pair of peak positions corresponding to the waveform period. . By such exclusion, the section detecting means can efficiently detect a pair of peak positions corresponding to the waveform period, that is, the same waveform section. Therefore, it contributes to the efficiency of the sound signal analysis processing.

A sound signal analyzer according to the present invention according to claim 9 of the present application is an input means for inputting an arbitrary sound signal, and a peak position for detecting a peak position of the input sound signal. Detecting means, and the degree of coincidence of the waveforms of any two adjacent sections among various sections obtained by dividing the waveform of the sound signal between any two peak positions detected by the peak position detecting means. And a first section detecting means for connecting sections having a high degree of coincidence to each other to detect a first same waveform section group, and a start section and a last section in the first same waveform section group. As the comparison target section, the degree of coincidence of the waveform is calculated for each of the adjacent sections before and after the first same waveform section group, and the first same waveform section group is calculated based on the calculated degree of match. And extend this to A second section detecting means for detecting as a second same waveform section group, and a steady section detecting means detecting a steady section for sound signal analysis based on the second same waveform section group detected by the second section detecting means. It is equipped with. This configuration is such that the first same waveform section group detected by the first section detection means is extended before and after the first same waveform section group by the second section detection means to detect a steady section for sound signal analysis. Features. That is, if the degree of coincidence is set to be low, the waveform section becomes too wide, and it becomes difficult to detect a steady section. However, if the degree of coincidence is set high, the same waveform section will be sparse. Therefore,
With the degree of coincidence of the first section detection means set to a high value, the first same waveform section group is once detected, and the second section detection means is used to set a section before and after the first same waveform section group. Is expanded so that the same waveform section can be detected efficiently.

In one embodiment of the sound signal analyzing apparatus according to the ninth aspect, the sound signal analyzing apparatus is provided between any adjacent ones of the second same waveform section group detected by the second section detecting means. When there is a gap section that does not belong to, the degree of coincidence between the last section of the second same waveform section group on the front side and the gap section adjacent thereto and the start section of the second same waveform section group on the rear side and the adjacent section thereof Alternatively, the degree of coincidence with the gap section may be determined, and the higher degree of coincidence may be incorporated into the front or rear second identical waveform section group. Second
As a result of the expansion by the section detection means, if there is a section that does not belong to any of the second same waveform section groups, it is incorporated into any one of the same waveform section groups. In addition, there are various methods of incorporating, and the degree of coincidence may be sequentially compared based on the last section of the second same waveform section group on the front side and the start section of the second same waveform section group on the rear side. Similar processing may be performed with the incorporated section as the last section or the start section. Alternatively, a limit value may be provided for the degree of coincidence, and if the degree of coincidence is too low, the section may not be incorporated in either of the sections.

The sound signal analyzing apparatus according to the present invention described in claim 12 at the time of filing is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided for each predetermined section with respect to the sound signal. Pitch detection means for detecting the pitch of each sound signal and generating a data string of the detected pitch,
Filter processing in which the pass band is time-varying controlled according to the frequency corresponding to each pitch in the pitch data string,
First filtering means for applying the input sound signal;
A period reference position detection unit for detecting a plurality of candidate positions serving as a period reference for the sound signal output from the first filter processing unit; a frequency corresponding to each pitch in the pitch data sequence and a frequency of a predetermined integer multiple thereof Second filtering processing means for performing a filtering process in which a pass band is subjected to time-varying control according to the input sound signal, and output from the second filtering processing means corresponding to the detected candidate position. A section detecting means for determining a degree of coincidence of a plurality of sections obtained by dividing the sound signal, and detecting a section having a high degree of coincidence as the same waveform section; Pitch analyzing means for analyzing the pitch of the sound signal based on the pitch.

The pitch detecting means and the first filter processing means perform time-varying filter processing on the sound signal in accordance with the pitch tendency of the input sound signal, whereby the fundamental wave component of the sound signal is reduced as much as possible. The waveform can be shaped to be as close to a sine wave as possible so as to be extracted.
Therefore, the process of detecting the candidate position to be the cycle reference for the input sound signal, which is performed by the cycle reference position detection means for the first filtered sound signal waveform, is as accurate as possible in the waveform cycle of the input sound signal. It will be performed in response. Therefore, the section can be accurately separated by the section detecting means. On the other hand, in the second filter processing means, a filter process in which a pass band is time-varying controlled according to a frequency corresponding to each pitch in the pitch data sequence and a frequency of a predetermined integer multiple thereof is applied to the input sound signal. Therefore, the sound signal waveform after the second filter processing includes not only the fundamental wave component but also an appropriate harmonic component, and appropriately maintains the characteristic of the waveform shape that fluctuates with time of the input sound signal. (However, since a complicated component is removed by filtering, it has a relatively simple waveform suitable for comparison processing.) Therefore, the section detecting means maintains a relatively accurate waveform shape, which is divided by a section corresponding to a relatively accurate waveform cycle.
However, a relatively simple shaped sound signal waveform suitable for comparison processing is compared for each section, and the degree of coincidence is determined, so that the processing of determining the degree of waveform coincidence is easy and the accuracy is good. It has the effect. That is, the section (the same waveform section) to be subjected to the pitch analysis can be detected with higher accuracy, and the accuracy of the sound signal analysis is improved.

The sound signal analyzing apparatus according to the present invention according to claim 13 of the present application provides a providing means for providing a continuous sample amplitude value of an arbitrary sound signal, First filter processing means for performing first filter processing of predetermined characteristics, and generating control frequency data for second filter processing based on the continuous sample amplitude values subjected to the first filter processing. Control data creating means for performing, the second filter processing means for performing a second filter processing of the characteristic based on the created control frequency data, to the continuous sample amplitude value provided by the providing means, Pitch detecting means for detecting a pitch of the sound signal based on the continuous sample amplitude values subjected to the second filter processing. As described above, by shaping the input sound signal by the two-stage filter processing means, it is possible to make the pitch detection easy to perform, and to improve the analysis accuracy.

The sound signal analyzing apparatus according to the present invention described in claim 10 at the time of filing is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided at every predetermined interval with respect to the sound signal. Pitch detection means for detecting the pitch of each sound signal and generating a data string of the detected pitch,
Based on a dynamic average of relative values obtained by the relative value conversion means for converting the difference between successive pitches in the pitch data sequence into relative values based on the cent value of the pitch. A dynamic reference calculating means for calculating a dynamic reference value, and comparing the relative value obtained by the relative value converting means with the dynamic reference value calculated by the dynamic reference calculating means. A stationary section detecting means for detecting a stationary section for analysis.

The difference between successive pitches in the pitch data sequence is converted into a relative value based on the cent value of the pitch, and a dynamic reference value (dynamic border) is calculated based on a dynamic average of the relative values. Then, the stationary section is detected by comparing the dynamic reference value with the relative value. The dynamic average is a cumulative average of the relative values of the respective pitches from a predetermined averaging start time to the present time, that is, an integrated average of the relative values of the pitches up to the present time. This dynamic average is used as a dynamic reference value or dynamic border. A dynamic border is a dynamic (ie, time-varying) boundary or reference value. In this manner, by creating a dynamic reference value (dynamic border) by dynamic averaging of relative values based on cent values, normalized comparison reference data (that is, dynamic border) for detecting a stable pitch section is obtained. And detection accuracy can be improved. For example, if the pitch difference between adjacent pitches, that is, the relative value is “0”, those pitches are the same pitch, and it is understood that sounds of the same pitch are continuous. Also, for example, if the condition is set such that the relative value “1” corresponds to the pitch of a semitone, for example, if the pitch difference between adjacent pitches, that is, the relative value is “1”, those pitches differ by a semitone. So you know that it's a completely different sound. Actually, the pitch is not so simple, and the pitch fluctuates appropriately even when the same sound is continuous. The dynamic border is used as a criterion value for detecting a portion that is stable in such a sound pitch that fluctuates as appropriate. In this way, if the pitch suddenly becomes unstable from a stable part, it can be detected that the part is a break in the steady section, while if the pitch fluctuates slightly in the part where the pitch is unstable, However, it can be determined that the changed portion is not a break of the steady section, and the steady section can be detected with a feeling closer to the human ear.

When the second section or the stationary section of the input sound signal is detected by using any one of the above-described various methods or a combination thereof, the detected second section is used. Alternatively, note analysis processing is performed for a steady section. That is, the sound signal analyzer according to the present invention analyzes the pitch of the sound signal in the second section or the steady section for analyzing the detected sound signal, and determines a note of the sound signal. An analysis means may be further provided.

The sound signal analyzing apparatus according to the present invention described in claim 14 at the time of filing is an input means for inputting an arbitrary sound signal, and the sound signal input from the input means is provided for each predetermined section. Pitch detecting means for detecting the pitch of each sound signal and generating a data sequence of the detected pitch,
Based on a dynamic average of relative values obtained by the relative value conversion means for converting the difference between successive pitches in the pitch data sequence into relative values based on the cent value of the pitch. A dynamic reference calculating means for calculating a dynamic reference value, and comparing the relative value obtained by the relative value converting means with the dynamic reference value calculated by the dynamic reference calculating means, to perform pitch analysis. A steady-state section determining means for detecting a steady-state section for use; a static reference calculating means for calculating a static reference value based on a static average of the relative values within the steady-state section; A pitch determining section detecting means for comparing the relative value within the section and calculating a pitch determining section for calculating the representative frequency of the steady section; and the pitch de-sampling section within the detected pitch determining section. Based on the data row is obtained comprising a frequency calculating means for calculating a representative frequency of the stationary section.

The static average is a simple arithmetic average of all the relative values in one stationary section, and is a constant value for the stationary section. This static average is used as a static reference value (static border). The static reference value (static border) is a static boundary value (that is, a comparison reference value) that does not fluctuate over the steady section. For example, if the relative value is equal to or smaller than the static border, the pitch determining section detecting means determines that the pitch related to the relative value belongs to the section with the most stable, and determines the section with the most stable pitch as the pitch. The section is determined. As described above, according to the present invention, when calculating the representative frequency, that is, the pitch of the steady section, the representative frequency is not calculated based on all the waveforms in the steady section, but is calculated based on the static border. The representative frequency of the stationary section is calculated on the basis of the pitch data in the set section, that is, the pitch determination section. As a result, the representative frequency of the steady section can be calculated with high accuracy.

The dynamic reference value calculating means multiplies the dynamic average of the relative values by a predetermined value, a value obtained by adding a predetermined value, or a predetermined value, and multiplies the product by a predetermined value. May be calculated as the dynamic border.

The stationary sections detected by the above-described methods do not always correspond to valid notes, and some of them may be invalid. According to the present invention, a grid divided at time intervals corresponding to a predetermined note length (for example, the minimum allowable note length) can be advantageously used to determine an invalid stationary section. That is,
The sound signal analyzer of the present invention arranges each of the determined stationary sections on a grid divided at a time interval corresponding to a predetermined note length in accordance with a time series thereof. Is assigned to each stationary section, and as a result, if a plurality of stationary sections are assigned to the same grid position, one stationary section having the longest time length is selected as a valid section. Means may be further provided. Similarly, the sound signal analyzing apparatus of the present invention described in claim 15 at the time of filing is an input means for inputting an arbitrary sound signal consisting of a time series of one or a plurality of notes, and 1 from the sound signal
A section detecting means for respectively detecting a section estimated to correspond to one note; and arranging the detected section on a grid divided at time intervals corresponding to a predetermined note length in accordance with the time series. Assigning one grid position closest to one predetermined end of the start or end end of each steady section to each steady section,
As a result, when a plurality of stationary sections are assigned to the same grid position, means for selecting one of the stationary sections having the longest time length as a valid note is provided.

Further, according to the present invention, the degree of coincidence between the waveforms of adjacent sections is calculated, a portion where the degree of coincidence is larger than a predetermined value is detected as a voiced section, and the degree of coincidence within the detected voiced section is detected. Based on the waveform of the high section, the degree of coincidence is sequentially calculated with the waveforms of the sections on both sides of the section, and a steady section is detected based on the degree of coincidence, and the pitch of the sound signal is analyzed for the steady section. / May be detected. Since a section having a high degree of coincidence in a voiced section serves as a reference for a vowel of a voice, a change in a vowel can be detected based on the degree of coincidence determined based on the vowel. The stationary section detected in this way is a vowel,
That is, it may be recognized as one note. In each configuration of the present invention described above, a section having a high degree of coincidence of waveforms, that is, a section determined as the same waveform section can be recognized and analyzed as a vowel section, that is, a single note chunk.

Further, in the present invention, each of the above-described configurations, that is, the invention, can be configured not only as a device invention of a voice analysis device, but also as a method invention of a voice analysis method. Further, the embodiment of the present invention can be implemented in the form of a computer program, and the present invention can be implemented in the form of a recording medium storing such a computer program. Included in the range.

[0037]

Embodiments of the present invention will be described below in detail with reference to the accompanying drawings. FIG. 2 is a hardware block diagram showing the configuration of an electronic musical instrument incorporating a musical sound information analyzer and a performance information generator according to the present invention. The electronic musical instrument is controlled by a microcomputer including a microprocessor unit (CPU) 1, a program memory 2, and a working memory 3. The CPU 1 controls the operation of the entire electronic musical instrument. This CPU1
, A program memory 2, a working memory 3, a performance data memory 4, a key press detection circuit 5, a microphone interface 6, a switch detection circuit 7, a display circuit 8, and a sound source circuit 9 are connected to each other via a data and address bus 1 E. Have been.

The program memory 2 stores various programs of the CPU 1 (such as system programs and operation programs),
It stores various data and the like, and is constituted by a read only memory (ROM). Working memory 3
Is a memory for temporarily storing performance information and various data generated when the CPU 1 executes a program. A predetermined address area of a random access memory (RAM) is assigned to each of the registers, flags, buffers,
It is used as a table or the like. Performance data memory 4
Is for storing performance information (MIDI data) generated based on an input sound from a microphone or the like. Further, the CPU 1 may be connected to a hard disk device 1H or the like, and may store various data such as automatic performance data and chord progression data, and may further store the operation program. The ROM 2
Without storing the operation program in the hard disk drive 1
By storing these operation programs in H and reading them into the RAM 3, it is possible to cause the CPU 1 to perform the same operation as when the operation programs are stored in the ROM 2. By doing so, it is possible to easily add an operation program or upgrade the version. Also, a removable external storage medium 1G, for example, a CD-ROM or the like may be provided. Various data and an arbitrary operation program may be stored in the external storage medium 1G, for example, a CD-ROM. The operation program and various data stored in the CD-ROM can be read out by a CD-ROM drive (not shown) and transferred to and stored in the hard disk drive 1H. This makes it possible to easily perform new installation and version upgrade of the operation program.

The communication interface 1F is connected to a data and address bus 1E, and can be connected to various communication networks such as a LAN (local area network) and the Internet via the communication interface 1F. Data may be exchanged between the devices. Thereby, when the operation program and various data are not stored in the hard disk device 1H, the operation program and various data can be downloaded from the server computer. In this case, an electronic musical instrument, which is a musical sound generation device serving as a client, transmits a command for requesting download of an operation program and various data to a server computer via a communication interface and a communication network. The server computer transmits predetermined operation programs and data to the electronic musical instrument 1 via the communication network in response to the command. The electronic musical instrument receives these operation programs and data via the communication interface and stores them in the hard disk device. Thus, the download of the operation program and various data is completed.

The keyboard 10 is provided with a plurality of keys for selecting the pitch of a musical tone to be pronounced, has a key switch corresponding to each key, and detects a key pressing speed as required. It has touch detection means such as a device and a pressing force detection device. The key press detection circuit 5 is configured to include a circuit composed of a plurality of key switches provided corresponding to each key of the keyboard 10 for designating a pitch of a musical tone to be generated, and a new key is pressed. When a key-on event is output,
When a key is newly released, a key-off event is output. In addition, a process of generating touch data by determining a key pressing operation speed or a pressing force at the time of key pressing is performed, and the generated touch data is output as velocity data. As described above, data such as a key-on event, a key-off event, and velocity are data conforming to the MIDI standard (hereinafter referred to as “MI
DI data ”) and includes data indicating the key code and the assigned channel. The microphone 1A converts an audio signal or a musical instrument sound into a voltage signal,
Output to the microphone interface 6. The microphone interface 6 converts an analog voltage signal from the microphone 1A into a digital signal and outputs the digital signal to the CPU 1 via the data and address bus 1E.

The numeric keypad and various switches 1B include a numeric keypad for inputting numerical data, a keyboard for inputting character data,
It is configured to include various operators such as a start / stop switch for a note conversion process (sound signal analysis process and performance information generation process). In addition, various controls for selecting, setting, and controlling pitches, timbres, effects, and the like are also included, but details thereof are publicly known, and thus description thereof is omitted. The switch detection circuit 7 detects the operation state of each operator of the numeric keypad & various switches 1B, and outputs switch information corresponding to the operation state to the CPU 1 via the data and address bus 1E. The display circuit 8 displays various information such as the control state of the CPU 1 and the contents of the setting data on the display 1C. The display 1C is a liquid crystal display panel (LCD)
, A CRT or the like, and the display operation thereof is controlled by the display circuit 8. GU is operated by this numeric keypad & various switches 1B and display 1C.
I (Graphical User Interface)
e) is configured.

The tone generator circuit 9 is capable of simultaneously generating musical tone signals on a plurality of channels.
, MIDI data on the musical sound track given via the input device, and generates a musical sound signal based on this data, and outputs it to the sound system 1D. The tone generator circuit 9 can simultaneously generate tone signals on a plurality of channels by using a single circuit in a time-division manner to form a plurality of tone channels, or a single tone channel is constituted by a single circuit. It may be of the type as described below. Also, any tone signal generation method in the tone generator 9 may be used. For example, a memory reading method (waveform memory method) for sequentially reading out tone waveform sample value data stored in a waveform memory in accordance with address data that changes according to the pitch of a musical tone to be generated, or a phase angle parameter An FM method for executing a predetermined frequency modulation operation as data to obtain tone waveform sample value data, or an AM for executing a predetermined amplitude modulation operation using the address data as phase angle parameter data to obtain tone waveform sample value data
A known method such as a method may be appropriately adopted. In addition to these methods, a physical model method that synthesizes a musical sound waveform by an algorithm that simulates the sounding principle of a natural musical instrument, a harmonic synthesis method that synthesizes a musical sound waveform by adding a plurality of harmonics to a fundamental wave, A formant synthesis method of synthesizing a musical tone waveform using a formant waveform having a specific spectral distribution, an analog synthesizer method using VCO, VCF, and VCA may be employed. Further, the present invention is not limited to the case where the tone generator circuit is configured using dedicated hardware.
The tone generator circuit may be configured by using the SP and the microprogram, or the tone generator circuit may be configured by a CPU and a software program. Sound source circuit 9
Is generated through a sound system 1D including an amplifier and a speaker.

Next, an example in which the electronic musical instrument according to the present invention operates as a sound signal analyzer and a performance information generator will be described. FIG. 1 is a diagram showing a main flow when the electronic musical instrument of FIG. 2 operates as a performance information generating device. The main flow is executed sequentially in the following steps. Step 11: First, an initial setting process is performed, and an initial value is set in each register, flag, and the like in the working memory 3 in FIG. At this time, when the musical note conversion start switch on the numeric keypad & various switches 1B is turned on, a series of processing from step 12 to step 18 is performed.

Step 12: This step is carried out when it is determined that the musical note processing start switch has been turned on. The input audio signal and the voltage waveform of the musical instrument sound are sampled at a predetermined period (for example, 44.1 kHz).
This is stored in a predetermined area in the working memory 3 as a digital sample signal. Since this sampling process is performed by a conventionally known method, the details are omitted here.
Steps 13 to 16 correspond to the note conversion process corresponding to the ON operation of the note conversion start switch. In this note conversion process, sampled audio signals and digital sample signals of musical instrument sounds are analyzed in various ways and converted into a pitch sequence, that is, MIDI data that can be displayed in a musical score. Step 13: Based on the digital sample signal obtained as a result of the audio sampling processing in step 12, an effective section detection process for detecting a section where a musical sound exists, that is, an effective section is performed. Details of the valid section detection processing will be described later. Step 14: As a result of the effective section detection processing in step 13, a stable section detection processing for subdividing each detected effective section into a stable section having a more stable level is performed. The details of the stable section detection processing will be described later. Step 15: As a result of the stable section detection processing in step 14, a steady section detection processing for detecting a steady part (a part corresponding to one note) of a musical sound present in each detected stable section is performed. The details of the stationary section detection processing will be described later. Step 16: As a result of the processing of steps 13 to 15, a pitch sequence determination process for allocating the most optimal note for each steady section obtained is performed. That is, in this step, MIDI data is generated. Details of the pitch sequence determination processing will be described later. Step 17: A score creation process for creating a score based on the MIDI data generated by the process of step 16 is performed. Since the score creation processing can be easily realized by the conventional technique, the details are omitted. Step 18: Perform an automatic performance process based on the MIDI data generated by the process of step 16. Since the automatic performance processing can be easily realized by the conventional technique, the details are omitted.

FIG. 3 is a diagram showing details of the valid section detection processing in step 13 of FIG. Hereinafter, how the effective section is detected from the digital sample signal obtained in step 12 will be described with reference to FIGS. 7 and 8. Step 31: An average sound pressure level is calculated based on the digital sample signal obtained in step 12. FIG. 7 is a diagram showing an example of a waveform value of a voice signal sampled at a sampling frequency of 44.1 kHz, that is, a digital sample signal. FIG. 7 shows waveform values for about 20 points. In step 31,
The average of the sample amplitude values over a predetermined number of samples (for example, the number of samples corresponding to a time equivalent to 10 msec) is obtained, and the average is used as the average sound pressure level. Therefore, in the case of the sampling period of 44.1 kHz, the predetermined number of samples is “441”, and the average value of a certain sample point is 10 m
It is the sum of the points before sec, ie, the sum of the waveform values 441 points before the last point divided by 441. Since there is no waveform value for 441 points from 0 point to 440 points,
The average of the waveform values from the point to the corresponding point is defined as the average value of the point. In this way, time-series average sound pressure level information is obtained for each sample timing.

FIG. 7 shows a case where the average value of the waveform values for 15 points is calculated as the average sound pressure level for convenience of explanation. Therefore, up to the first 15 points, the total value of the waveform values up to that point is divided by the number of points. The sum of the waveform values is obtained by summing the absolute values. FIG. 8A is a graph showing the average sound pressure level value obtained in this way, with the sampling point on the horizontal axis. Hereinafter, the curve formed by the average sound pressure level in FIG. 8A is referred to as an average sound pressure level curve. When the average sound pressure level is obtained every 15 points as shown in FIG.
A low-pass filter with a cutoff frequency of about 10 Hz is applied to smooth the level fluctuation. Therefore, when actually averaging the waveform values for 441 points, it is desirable to apply a low-pass filter having a cutoff frequency of about 80 to 100 Hz to smooth the level fluctuation. Also, here, a case has been described in which the average value of a certain sampling point is obtained, and the average sound pressure level is obtained by summing the waveform values of a predetermined number of points before that point. The waveform values at a predetermined number of points before and after may be totaled, or the waveform values at a predetermined number of points after the sampling point may be totaled.

Step 32: The average sound pressure level curve obtained in step 31 as shown in FIG. 8A is classified into an effective section or an invalid section based on a predetermined threshold value. In this process, the threshold value is set to 20% of the maximum waveform value in the average sound pressure level curve. It goes without saying that other values may be used as threshold values. For example, the average value of the average sound pressure level curve may be used as the threshold value, or the average value of the average value may be set to 80.
Percentage may be used as the threshold, or half the maximum value of the average sound pressure level curve may be used as the threshold. The threshold value is indicated by a dotted line as shown in FIG. Therefore,
The intersection point between the dotted line (threshold) and the average sound pressure level curve is a boundary between the effective section and the invalid section. . In FIG. 8B, the valid section is indicated by a circle, and the invalid section is indicated by a cross.

Step 33: If the minimum length required for human recognition of the pitch is 0.05 msec, an invalid section smaller than the minimum length is set as an effective section from the invalid sections determined in step 32. change. For example, when the sampling period is 44.1 kHz, invalid sections of 2205 or less in sampling number are changed to valid sections.
In FIG. 8B, the third and fifth invalid sections from the left correspond to this short invalid section. Accordingly, as a result of the processing in step 33, FIG. 8B becomes as shown in FIG. 8C, and the valid section is extended. In this process, the invalid sections existing at the beginning and end of the entire section correspond to short invalid sections, but are represented by special symbols that are not changed to valid sections just because they are short, using a triangle. doing.

Step 34: A process of changing a short effective section of 0.05 msec or less from the pattern of the effective section and the invalid section obtained as a result of the processing of the step 33 to an invalid section is performed. This process is performed in the same manner as in step 33. In FIG. 8C, the rightmost effective section corresponds to this short effective section. Therefore, step 3
As a result of the process 4, FIG. 8C becomes as shown in FIG. As is clear from FIG. 8D, the effective sections are all four sections from the first section to the fourth section. In addition,
A mark at the end of the section is regarded as a fourth valid section. Step 35: The average value of the average sound pressure level curve of the effective section specified in step 34 is obtained, and if the average value is smaller than a predetermined value, a final effective section in which that part is regarded as an invalid section is checked. This average value is obtained by dividing the sum of the average sound pressure level values of the points existing in the effective section by the effective section length. The average value of the average sound pressure levels obtained in this manner is shown below each section in FIG. The first section is 60, the second section is 2
5, the third section is 45, and the fourth section is 15. If the average value of the average sound pressure level falls below 30% of the maximum waveform value of the section, the section is regarded as an invalid section.
Here, since the second section and the fourth section correspond to each other, each section becomes an invalid section. FIG. 8E is a diagram showing the valid section and the invalid section specified by the valid section check processing in step 35.

Step 36: Steps 31 to 3
A process for extending the valid section specified by the processes up to 5 is performed. For example, as shown in FIG. 8F, 15% of the maximum waveform value is set as the extension permission level, a line is drawn on that portion, and the boundary line specifying the effective section is extended to the line of the extension permission level. . In other words, the extension process is performed while checking whether the average sound pressure level curve has fallen below the extension permission level while checking the rise and fall of the average sound pressure level curve from the end of each effective section to the outside. At this time, when the descending is reversed to the ascending or when the descending is below the extended permission level, the area up to that point is regarded as an effective section. FIG. 8G is a diagram showing another example of the effective section extension processing. The extension permission level is set to 5% of the maximum waveform value, and the position where the lowering of the average sound pressure level curve ends is set as the end of the effective section. Alternatively, the position where the rise has started may be set as the end. According to this extension processing, FIG.
The extension width of the first section and the third section is larger than in the case of (F). In this way, an effective section that can be recognized as a pitch by a human is finally determined.
If the extension permission level is low and the effective section is at a short distance, the extension position at the end of a certain effective section may be close to the extension position at the beginning of the next effective section. It may also be at the same position. In addition, the boundary position changes depending on whether a part where the descent ends or a part where the ascent starts is delimited. If the effective sections overlap as a result of this extension processing, both intermediate positions may be set as boundary positions. Note that in FIGS. 8F and 8G,
Although the case where the effective section is extended before and after has been described,
Only the front direction or the rear direction may be used. Further, when extending forward and backward, the extension permission level may be different between the forward direction and the backward direction.

FIG. 4 is a diagram showing details of the stable section detection processing in step 14 of FIG. Hereinafter, a stable section detection process is performed on the average sound pressure level curve in the effective section obtained in step 13 to detect a region where the level is stable. The operation of the stable section detection processing will be described with reference to FIG. FIG. 9 is a view showing the first point from point A to point B in FIG.
Is shown for the case where a stable section is detected for the valid section of FIG. Step 41: The slope frequency is calculated based on the average sound pressure level curve in the effective section detected in FIG. In this process, as shown in FIG. 9B, the calculation width for calculating the inclination is, for example, 100 points, and the shift amount of the calculation width is, for example, 50 points, and the shift from point A to point B is sequentially performed. While calculating the inclination frequency. Assuming that the point A is the sample point "000", the slope between the sample points "000" and "100" is calculated, and then the slope is shifted by 50 points between the sample points "050" and "150". Obtain the slope frequency. For example, the average sound pressure level of the sample point “000” is “325” and the sample point “1” is
When the average sound pressure level of “00” is “1576”, the slope frequency is (1576-325) /100=12.5
It becomes 1. Thereafter, sample points “100” and “20”
0 "," 150 "and" 250 "," 20 "
The slope frequency is calculated in order, such as between "0" and "300". FIG. 9B shows an example of the calculated inclination degree. As is clear from the figure, the sample point “00”
The gradient between 12.0 and 100 is 12.51, and the gradient between sample points 050 and 150 is 32.1.
42, the slope between sample points "100" and "200" is 20.12, sample point "150",
The slope between “250” is 11.84, the slope between sample points “200” and “300” is 5.24, the slope between sample points “250” and “350” is 4.82, and the sample point The gradient between “300” and “400” is 2.34, and the sample point “350”,
The gradient between “450” is 3.89, and the gradient between sample points “400” and “500” is 5.36. These gradients will be stored as the gradients at the former sample point. That is, the slope frequency of the sample point “000” is 12.51, and the slope frequency of the sample point “050” is 32.42, and the slope frequency is stored for each sample point. In this way, the gradient frequencies in all the sections from the point A to the point B are calculated, and the stable section extraction processing in the next step 42 is performed.

Step 42: Based on the gradient calculated in step 41, a stable section is extracted this time.
In other words, when the slope frequency at each sample point is equal to or less than a predetermined value (for example, 10) as a stable portion, and the number of sample points regarded as the stable portion is equal to or more than a predetermined number, that is, for a predetermined time, Then, the continuous stable portion is defined as a stable section. The predetermined time is set to, for example, about 2000 sample points in consideration of the tempo. In the case of the average sound pressure level curve as shown in FIG. 9A, three locations a, b and c as shown in FIG. 9C are searched for as stable sections. Step 43: Based on the existence of the stable section extracted in step 42, the human first notices that there is a starting point of the note trigger sound near the starting point of the stable section. Here, in order to determine the vicinity of the starting point of the note, the stable section extracted in step 42 is extended. When extending this stable section, that is, when determining the start point of a note, for the first stable section a, the point A is necessarily the start point of the note in the stable section a, and for the last stable section c, Inevitably, point B is the end point of the note in the stable section c. However, the note end point of the stable section a and the note start point of the stable section b cannot be easily obtained. Therefore, the sample point having the largest inclination between the end point of the stable section and the start point of the next stable section is determined as the note end point of the stable section and the note start point of the next stable section. The note end point of each stable section a and the note start point of stable section b become point C as shown in FIG. 9D, and the note end point and stable section c of stable section b.
The note start point is point D. Note that, in the above description, the case where the sample point with the largest inclination is the note start point of the stable section and the note end point of the next stable section has been described. However, the present invention is not limited to this. The sample point when the stability degree first exceeds a predetermined value (threshold value) up to the start point of the stable section may be the note end point (note start point), or the start point of the stable section. A sample point in the case where the value falls below a predetermined value (threshold value) immediately before may be set as a note end point (note start point), or a sample point obtained by the above three methods may be compositely calculated and newly calculated. Alternatively, the note end point (note start point) may be obtained. The sections AC, CD, and DB obtained in this manner become stable sections corresponding to the respective levels. That is, in the case of FIG. 9, the stable section corresponding to the level of the stable section a is AC, the stable section corresponding to the level of the stable section b is CD, and the stable section corresponding to the level of the stable section c is DB.

FIG. 5 is a diagram showing the details of the stationary section detection processing in step 15 of FIG. How the steady section is detected from the stable sections determined in step 14 will be described in detail with reference to FIGS. 10 to 17. When analyzing musical audio signals such as voices and musical sounds, it is important to know where the stationary part is. For non-rhythm sounds, the pitch is determined by the periodicity of the stationary part.
This is because the sound value is determined using the stationary part as a skeleton. In this embodiment, the stationary part is a section corresponding to one note when expressed as a musical score. Means to detect on the time axis a section recognized as. Hereinafter, the stationary section detection processing will be described according to the steps in FIG.

In order to detect a stationary section, it is necessary to first detect a reference position of the period of the sound signal waveform. The method of detecting the reference position can be roughly divided into one generally using either the 0 cross position detection method or the peak position detection method. In order to detect the reference position of the cycle by the 0 cross position detection method, it is difficult to detect the overtone without removing as much as possible of the overtone with a filter or the like, and band division is also required. In the case of the peak position detection method as well, it is desirable to remove harmonics as much as possible, but since it is not as severe as the 0 cross position detection, it is only necessary to apply a band-pass filter with the cut-off frequency of the audible frequency band of the voice or instrument. There is no particular need to perform such processing. Therefore, the peak position detection method is simpler in procedure, and a method that can obtain a reasonable result is desirable. Therefore, in this embodiment, the case where the reference position of the cycle is detected by the peak position detection method will be described.

Step 51: A predetermined harmonic is deleted by passing through a first-order band-pass filter (first-order BPF). This is to apply a band-pass filter using a soundable band as a cutoff frequency. In the case of voice, the band that can be pronounced by a human is about 80 to 1000 Hz, and this is necessary for analyzing almighty without limiting the user. However, when the number of users is limited, it is possible to reduce errors due to overtones and improve the detection accuracy by narrowing the soundable band to some extent. 80-700Hz for guitar
However, if the pitch frame is determined in advance, the accuracy is improved. The accuracy can be improved by setting in advance the differences for each instrument. FIG. 10A shows a part of the audio waveform after the first BPF processing. Step 52: A peak reference position detection process, which is a reference for one cycle, is performed on the musical tone waveform signal obtained by the first-order BPF process of step 51 using a peak position detection method. This peak position detection method is performed by a known method. The peak level of the musical tone waveform is detected and held by a predetermined time constant circuit, and the held value is set as a threshold voltage. 10A by sequentially repeating the process,
Can be detected. FIG.
(A) is a diagram showing a state of a threshold hold voltage when detecting this peak position. From the audio waveform of FIG. 10A, a peak position as shown in FIG. 10B is detected. In FIG. 10B, the peak reference position P
1, P2, P3, and P6 regularly appear at predetermined positions, but peaks appear at peak reference positions P4 and P5 at positions including errors due to slight disturbance of the audio waveform. This is because the peak position appears continuously as shown in FIG. 10A because the band of the cutoff frequency of the first-order BPF processing in step 51 covers a wide range.

Step 53: Based on the peak reference position detected in step 52, a basic section starting from a certain peak reference position and a section up to the next peak reference position immediately after the basic section (hereinafter referred to as a moving section). ) Are compared with each other to determine whether or not the waveforms are the same in the two sections. Considering the peak reference position shown in FIG. 10B, a section d is from the peak reference position P1 to the peak reference position P2, and a section e is from the peak reference position P2 to the peak reference position P3. At this time, both sections d,
Since e is larger than the minimum band length and smaller than the maximum band length, the section d is a basic section, the section e is a moving section, and is subjected to a waveform comparison process described later. Next, section e
Is a basic section, and a section from the peak reference position P3 to the peak reference position P4 is a section f. At this time, both sections e and f
Is larger than the minimum band length and smaller than the maximum band length, so that the section e becomes a basic section and the section f becomes a moving section, and is subjected to a waveform comparison process described later. However, since the section from the peak reference position P4 to the peak reference position P5 is smaller than the minimum bandwidth, the section g from the next peak reference position P5 to the peak reference position P6 is not a section to be compared. f is a waveform comparison target.
As a result of the waveform comparison processing, the sections f and g are recognized as different waveforms from the other sections d and e. First, the working memory (RAM) is provided with a data area in which a match flag or a non-match flag is written, using the peak reference position information as an address. Then, in the case as shown in FIG. 10B, since it is determined that the section d and the section e match, a match flag is written in the data area related to the peak reference position information P2 corresponding to the section e. On the other hand, since it is determined that the section e does not match the section f, a mismatch flag is written in the data area related to the peak reference position information P3 corresponding to the section f. Since the section from the peak reference position P4 to the peak reference position P5 is smaller than the minimum bandwidth, a mismatch flag is written in the data area related to the peak reference position information P4 and P5. It is assumed that a match flag has been written in the data area relating to the peak reference position information P1 and P6. FIG. 10C shows the state of the match flag and the mismatch flag which are sequentially written together with the peak reference position information.

The waveform comparison processing is performed by a method for calculating an error rate, which will be described later. FIG. 13 is a diagram for explaining a method of calculating an error rate performed in the waveform comparison processing. First, two waveforms for which the error rate is calculated are shown in FIG.
It is assumed that the comparison wave 1X and the comparison wave 2X as shown in FIG. This waveform is a range divided by the peak reference position in FIG. First, regarding the comparison wave 1X and the comparison wave 2X,
The amplitude value is normalized so that the maximum amplitude value becomes 100%. First, the comparison wave 1X becomes the comparison wave 1Y, and the comparison wave 2X becomes the comparison wave 2Y. Here, comparison wave 2
Since X has a shorter length in the time axis (horizontal axis) direction than the comparative wave 1X, the comparative wave 2X extends so as to have the same time width as the comparative wave 1X. That is, the time axis of the comparison wave 2Y is extended to make the comparison wave 2Z. The error rate is calculated between the comparison wave 1Y and the comparison wave 2Z. FIG. 13 is a diagram showing specific values when calculating the error rate between the comparison wave 1Y and the comparison wave 2Z. In the figure, a case will be described in which the error rates are calculated for the waveforms of the first cycle of the comparison wave 1Y and the comparison wave 2Z, that is, for 24 sampling waves. The difference is calculated for the same sampling position of the comparison wave 1Y and the comparison wave 2Z, and the sum of the absolute values of the difference is calculated. FIG.
In the case of 3, the total value of the absolute values is 122. By dividing this by the sampling number 24, the error rate is obtained. In this case, the error rate is 5. Therefore, if the threshold value of the same waveform is set to 10, the error rate 5 in the case of FIG. 13 is 10 or less, so that the same waveform is processed. In FIG. 13, each waveform is normalized with 1000 as the maximum level.

Step 54: Using the result of the waveform comparison processing in step 53, the sections in which the error rate is smaller than a predetermined value (for example, 10) are connected to each other to make a pseudo matching section. The maximum value and the minimum value of the extracted pitch are detected, and the cutoff frequency band is determined based on the maximum value and the minimum value. For example, suppose that the minimum value of the pitch in a plurality of matching sections obtained as a result of the waveform comparison processing is 235 points, and the maximum value is 365 points. Assuming that the minimum value is reduced by 10% and the maximum value is increased by 10% in order to give a margin to this coincidence section, the coincidence section becomes from about 212 points to about 402 points.
Become a point. This means that the sampling frequency is 44.
If it is 1 kHz, it corresponds to a frequency band of an audio signal of 110 Hz to 208 Hz. Accordingly, the cutoff frequency band is from 110 Hz to 208 Hz. Step 55: Using the new cut-off frequency band determined in Step 54, the signal is passed through a second-order band-pass filter (second-order BPF) to remove unnecessary harmonics. For example, in the above case, the cutoff frequency band is 110H
The range is from 208 to 208 Hz. As a result, errors due to harmonics can be reduced, and the detection accuracy can be improved. Step 56: The same processing as the peak reference position detection processing of step 52 is performed. Step 57: The same processing as the waveform comparison processing of step 53 is performed. By a series of processes from step 55 to step 57, low frequencies and harmonics that cause an error are cut, and a more accurate peak reference position detection process and a waveform comparison process can be performed. A section is obtained. By the waveform comparison processing of step 57, FIG.
As shown in FIG. 10C, a pitch sequence such as three steady intervals X, Y, and Z as shown in FIG. 10D is obtained from a waveform of an effective section characterized by a match flag and a mismatch flag.

Step 58: The pitch sequence as shown in FIG. 10D obtained by the processing up to step 57 may be used, but in order to further improve the accuracy, the pitch data at each peak reference position is interpolated. , Interpolation is performed so that one pitch data is obtained for each sample point. In this case, as apparent from FIG. 10 (A), for the sample points before the first peak reference position and the sample points after the last peak reference position, since there is no pitch data for interpolation, the pitch Interpolation cannot be performed. Therefore, pitch data at the first peak position is applied to the sample points before the first peak reference position, and pitch data at the last peak position is applied to the sample points after the last peak reference position. Then, between the respective peak reference positions, the values of both pitch data are linearly interpolated and applied. For example, in FIG. 10B, the pitch data of the peak reference position P1 is PD1,
Assuming that the pitch data at the peak reference position P2 is PD2, the pitch data at an arbitrary sample point PV between the peak reference positions P1 and P2 is obtained by the following equation. (PD2-PD1) x (PV-PA) / (P2-P1)

Step 59: Band-pass filter processing is performed using the pitch data for each sample point obtained by the processing of step 58. That is, since the pitch data changes with the passage of time, the so-called time-varying band-pass filter (BPF) processing in which the cutoff frequency band also varies with time is performed. As a result, the tone waveform signal is deformed into a waveform close to a sine waveform. By performing peak position detection processing on such a waveform, ideal peak position detection can be performed. In addition, since the comparison process can be performed based on this, the error can be minimized, so that the same waveform (same vowel) section can be found with high accuracy. Step 5A: The same processing as the peak reference position detection processing in step 52 is performed on the musical tone waveform that has undergone the time-varying BPF processing in step 59. Step 5B: The same processing as the waveform comparison processing in step 53 is performed on the musical tone waveform that has undergone the time-varying BPF processing in step 59.

In the above description, in steps 52, 56 and 5A of the stationary section detection processing in FIG. 5, the case where the peak reference position is detected by focusing only on the plus side of the musical sound waveform has been described. A musical sound waveform having a pitch, such as a sound, may have strong peaks on both the plus side, the minus side, and both the plus side and the minus side. Therefore, as described above, when a peak appears strongly on the plus side, the pitch can be detected by focusing on the plus side and detecting the peak reference position. in this case,
There is no problem when sharp peaks appear on both sides, but they sometimes appear strongly on the negative side. In such a case, it is needless to say that it is better to detect the peak reference position by paying attention to the strong appearance side. If the peak reference position is detected by paying attention to the direction in which the peak appears weakly, the detection of the peak reference position itself becomes ambiguous, and the pitch may not be detected as expected. The phenomenon that the peak appears to be biased to either the plus side or the minus side varies variously depending on the conditions of the sounding person or instrument at each time, so if you focus on either side and detect the peak reference position At present it is not possible to say that it is good. Therefore, the tone waveform is checked in advance so that a strong peak may appear on either side, and whether the peak appears strongly on the plus side or the minus side is detected, and based on the tone waveform on the detected side. Then, the peak reference position and the pitch may be detected. For example, it is assumed that the tone waveform in the stable section after the first-order BPF processing in step 51 in FIG. 5 is as shown in FIG. In the case of this tone waveform, a strong peak appears on the minus side, and a weak peak appears on the plus side. When the peak reference position is detected on both sides of this musical tone waveform, the peak intensity is different, but stable peaks appear on both sides. It is possible to detect the reference position. Therefore, in the case of this musical tone waveform, there is no problem even if the stationary section detection processing of FIG. 5 is performed by focusing on the plus side. However, depending on the musical sound waveform, in the case of a waveform having a relatively short cycle and a long repetition, the peak may gradually become dull. When the stationary section processing is performed by paying attention only to the plus side, In some cases, an accurate peak reference position cannot be detected. Therefore, even in the case of the waveform as shown in FIG. 11, it is desirable to pay attention to the minus side where the strongest peak appears. Therefore, for each stable section detected by the stable section detection processing of FIG. 4, it is detected whether the maximum of the absolute value of the musical tone waveform exists on the plus side or the minus side in the entire section, and attention is paid to the side on which the detection is performed. Then, the peak reference position may be detected. In the case of FIG. 11, since the maximum of the absolute value exists on the minus side, it is desirable to detect the peak reference position by paying attention to the minus side. This makes it possible to detect the peak reference position without being disturbed by harmonics or the like.

In the above-described embodiment, the peak level of the tone waveform is detected and held by a predetermined time constant circuit, and the held value is set as a threshold hold voltage. The case where the voltage is equal to or higher than the hold voltage is held as the next peak level, and the peak position is detected by sequentially repeating the level.
However, according to this method, it is determined whether or not a desired peak reference position can be detected depending on how much the time constant is set. In the case of a sound, there is a problem that an orderly peak often does not easily appear. Therefore, in the above-described embodiment, the determination whether or not the detected peak reference position is an accurate one that can be used in the subsequent frequency band determination processing is performed by the waveform comparison processing based on the detected peak position. Had gone by. This means that the peak position detected by the above-described peak reference position detection process may not be very accurate. Therefore, when detecting the peak level of the musical sound waveform, the time constant is set to a small value to some extent, a large number of possible peak reference positions are extracted from the musical sound waveform, and based on the extracted peak reference position. A waveform comparison process may be performed to sequentially determine the peak reference position. In this case, if the peak positions are detected by paying attention to the plus side of the musical tone waveform as shown in FIG. 14, three peak positions are extracted in one cycle.
When the waveform comparison processing is performed based on the three peak positions per one cycle, the time required for the processing becomes very long. Therefore, here, based on the section determined to have the same waveform, the subsequent detection processing of the same waveform section is performed efficiently. For example, in the case of a musical tone waveform as shown in FIG. 14, Pa to Po are detected as peak positions. Therefore, the waveform comparison processing is first performed for the following 16 combinations starting from the peak position Pa. (Pa-Pb) and (Pb-
Pc), (Pa-Pb) and (Pb-Pd), (Pa-P
b) and (Pb-Pe), (Pa-Pb) and (Pb-P)
f), (Pa-Pc) and (Pc-Pd), (Pa-P
c) and (Pc-Pe), (Pa-Pc) and (Pc-P)
f), (Pa-Pc) and (Pc-Pg), (Pa-P
d) and (Pd-Pe), (Pa-Pd) and (Pd-P)
f), (Pa-Pd) and (Pd-Pg), (Pa-P
d) and (Pd-Ph), (Pa-Pe) and (Pe-P
f), (Pa-Pe) and (Pe-Pg), (Pa-P
e) and (Pe-Ph), (Pa-Pe) and (Pe-P)
i) As a result, the section (Pa-Pd) and the section (Pd-P
It is determined that the waveforms in g) match. As a result, the peak position Pa becomes the pitch reference position PPa, and the other peak positions Pb and Pc are excluded from the candidates. Then, waveform comparison processing is performed for 16 combinations in the same manner starting from the peak position Pd, and the peak position Pd becomes the pitch reference position PPd. Hereinafter, similarly, the pitch reference positions are successively detected. When the same waveform section is detected from the 16 patterns, the error rates of all 16 patterns are calculated, and the smallest one having an error rate equal to or less than a predetermined value (for example, 10) is set as the same waveform section. Good
When an error rate that is less than or equal to a predetermined value (for example, 10) appears in the sequentially calculated error rates, it may be set as the same waveform section.

As described above, it takes a considerable amount of time to calculate the error rate for a large number of combinations in order to extract the same waveform section. Therefore, here, the same waveform section is used as described above. Based on the sections that have been certified as
Thereafter, the same waveform section is detected. That is, (Pa-Pb) and (Pb-Pd), (Pa-Pb) and (Pb-Pe) among the 16 combinations described above.
(Pa-Pb) and (Pb-Pf), (Pa-Pc) and (Pc-Pd), (Pa-Pc) and (Pc-Pg),
(Pa-Pd) and (Pd-Pe), (Pa-Pd) and (Pd-Pf), (Pa-Pe) and (Pe-Pf),
No comparison processing is performed for the nine cases (Pa-Pe) and (Pe-Pg). This is because the ratio of the waveform section lengths to be compared is almost twice, and it is impossible to obtain the same waveform without comparison, so that those comparisons are not performed in advance. Therefore, here, the waveform comparison processing is performed for the following seven combinations. (Pa-Pb) and (Pb-
Pc), (Pa-Pc) and (Pc-Pe), (Pa-P
c) and (Pc-Pf), (Pa-Pd) and (Pd-P
g), (Pa-Pd) and (Pd-Ph), (Pa-P
e) and (Pe-Ph), (Pa-Pe) and (Pe-P)
i) Then, it is determined that the waveforms of the section (Pa-Pd) and the section (Pd-Pg) match as in the case described above. As a result, the peak position Pa becomes the pitch reference position PPa, and the other peak positions Pb and Pc are excluded from the candidates. Next, the waveform comparison process is performed for the seven combinations in the same manner starting from the peak position Pd. Here, based on the interval (Pd-Pg), the next interval to be compared is determined. limit. That is, the section (Pd−
Pg) (Pg−P)
i), (Pg-Pj) and (Pg-Pk) are subjected to waveform comparison processing. Here, as α, for example, the section (Pa
Use about a quarter of the length of -Pd). It goes without saying that other appropriate values may be used for α. As a result of this waveform comparison processing, the section (Pd-Pg) and the section (Pg-Pj) are determined to be the same waveform section. Therefore,
Thereafter, since the waveform comparison process may be performed for the three combinations, the calculation process becomes very easy.

Step 5C: The stationary section obtained by the processing from step 51 to step 5B is extended.
That is, as a result of performing the processing from step 51 to step 5B, it is good that each of the stationary sections X, Y, and Z is separated by one non-matching section as shown in FIG. When the stationary section is divided by a plurality of non-coincidence sections as in C), each non-coincidence section must be connected to the normal section to extend the normal section. This step 5C is for performing the process of extending the steady section. For example, when one stable section is determined to have the same waveform section of the first same vowel portion XX and the second same vowel portion YY as shown in FIG. A first period section S1 of the first vowel portion XX in contact with the beginning of the section;
The last period section E2 of the second vowel portion YY that is in contact with the end of the stable section may be extended along the stable section. However, the non-coincidence sections N1 to N6 between the first vowel portion XX and the second vowel portion YY cannot be simply expanded, and are expanded as follows. First, based on the expansion error rate having a larger error rate tolerance than the waveform comparison processing of steps 53, 57, and 5B, the last period section E1 of the first same vowel portion XX and the non-coincidence sections N1, N2,
N3, N4, N5, and N6 are compared in this order, and the non-coincidence section determined to be smaller than the error rate for expansion is determined by the first vowel part XX.
Incorporate and extend. Similarly, the first period section S2 of the second vowel portion YY and the non-coincidence sections N6, N5, N4, N3, N
The comparison is made in the order of N1 and N1, and the unmatched section determined to be smaller than the error rate for expansion is incorporated into both of the same vowel parts XX and YY for expansion. In the case of FIG.
Suppose that N1 and N2 are incorporated in the first vowel part XX, and the non-matching section N6 is incorporated in the second vowel part YY, and as a result, as shown in FIG. The unmatched sections N3, N4, and N5 remaining without being incorporated into each of the homologous vowel sections are incorporated into any of the vowel sections as follows. An error rate is obtained by performing a waveform comparison process between the mismatched section N3 and the mismatched section N2 incorporated in the first vowel section XX, and the mismatched section N5 and the mismatched section incorporated in the second same vowel section YY. The error rate is obtained by performing a waveform comparison process with N6, the two error rates are compared, and the one with the smaller error rate (the one with a higher degree of coincidence) is incorporated as the same vowel part and expanded. As a result, since the error rate between the mismatched section N2 and the mismatched section N3 is smaller, FIG.
, The non-matching section N3 is incorporated in the first same vowel part XX. This time, the error rate between the non-matching section N2 and the non-matching section N4 is determined, and the smaller error rate is compared with the error rate between the mismatching section N6 and the mismatching section N5. In this way, as shown in FIG.
4 is incorporated in the first vowel part XX, and the non-matching section N5 is incorporated in the second vowel part YY. At the time when the non-matching section N3 is incorporated into the first same vowel section as described above, as shown in FIG.
It is needless to say that the non-coincidence section N4 and the non-coincidence section N3 at the time of calculating the next error rate may be regarded as the comparison target sections assuming the same vowel section. When incorporating the smaller error rate into any of the same vowel sections, an upper limit value is provided for the error rate. If the error rate exceeds the upper limit, the mismatched section is incorporated into the same vowel section. It may not be necessary. As described above, the gap section is incorporated into the same vowel section on both sides, and the extended processing of the steady section is completed.

In the above-described waveform comparison processing, the tone waveform subjected to the time-varying BPF processing in step 59 is
The case where the waveform comparison process of step 5B is performed has been described. In this case, since the comparison process is performed on a waveform close to the sine waveform after the BPF process, even the feature of each vowel is filtered. As a result, there is a possibility that the significance of extracting the same vowel section is weakened. Therefore, a waveform for peak position detection and a waveform for waveform comparison processing may be separately prepared, and the peak position detection and waveform comparison processing may be respectively performed based on the waveforms. In other words, the waveform after the time-varying BPF process is used as it is as the waveform for peak position detection, and the
A BPF-processed waveform that leaves a frequency band waveform with a period several times the frequency component used in the F process is used. For example, when the frequencies of the respective waveform section lengths are obtained based on the peak reference positions detected by the peak reference position detection processing in step 5A, it is assumed that the following frequency sequence is obtained. 134.6 Hz, 135.2 Hz, 1
45.7 Hz, 135.7 Hz,... Therefore, this frequency sequence is used as a basic frequency sequence, and time-varying BPF processing is performed for each frequency band with a frequency band that is an integral multiple thereof as a cutoff frequency. Are synthesized. That is, in the case of the above-described frequency train, 269.2 is set as a frequency train twice as large as the fundamental frequency train.
Hz, 270.4 Hz, 291.4 Hz, 271.4H
.., 403.8 Hz, 4
05.6Hz, 437.1Hz, 407.1Hz, ...
538.4 Hz, 540.8 as a quadruple frequency train
, And the time-varying BPF processing is performed separately using a frequency sequence that is an integral multiple of the fundamental frequency sequence as a cutoff frequency, such as Hz, 582.8 Hz, 542.8 Hz,. The BP corresponding to each frequency train obtained in this way
The combined waveform obtained by combining the waveforms after the F processing is used as the target waveform of the waveform comparison processing in step 5B. This makes it possible to accurately detect a vowel section in accordance with a change in timbre (vowel) when detecting a vowel section. It goes without saying that band-pass filter processing may be performed in which the basic frequency is set to the lowest frequency and the integral frequency of the basic frequency is set to the highest frequency, and this may be used as a target waveform for the waveform comparison processing.

Step 5D: The stationary section obtained by the processing from step 51 to step 5C is subdivided in consideration of the change in pitch and stability, and the final stationary section is determined. In the stationary section detection processing up to step 5C, since the waveform is expanded and compared, even if the pitch change of the speech waveform is caused by a continuous vowel such as "Oh", it is regarded as one and the same sound. It is a mechanism. Therefore, in the case of the musical sound waveform of the musical instrument sound, a situation may occur in which the pitch change of the continuous musical instrument sound cannot be found. Therefore, in this embodiment,
The state of the pitch change is checked for each steady part section obtained by the processing up to step 5C, and it is determined whether or not it is necessary to further divide it according to the state. If it is determined that it is necessary, the steady section is divided into smaller steady sections. That is, the frequency at the peak reference position is calculated by calculating the length (period length) between the peak reference positions in a certain stationary section and dividing the sampling frequency by that. Based on the value of the frequency of each waveform constituting each stationary section, the difference (ie, ratio) between the frequency f _{1 of} that waveform section and the frequency f ₀ of the previous waveform section
Is expressed as a relative value x based on a value quantified on a linear axis corresponding to a note, that is, a “cent pitch value”. f ₁ / f ₀ = 2 ^{(x / 12) When} this is expressed in logarithm and x is solved, it can be obtained by the equation x = log (f ₁ / f ₀ ) / log ( ¹² √2). In addition, ^"12 √2" is a 2 of the 12 root. As is well known, this corresponds to a formula that converts the difference or ratio (ie, pitch) of two frequencies to a cent value. However, in the expression of a typical cent value, the pitch of a semitone is expressed by 100 cents. However, for x according to the above equation, the numerical value “1” corresponds to the pitch of the semitone, and the pitch of the semitone is “1”. , The value including the value after the decimal point. However, since this is only a matter of the scale of the decimal point, the relative value x may be considered to substantially correspond to a cent value, that is, relative pitch information. . In the above equation, the relative value x is f ₁
And it will have a positive or negative sign by either the larger f _0, because for the detection of pitch stable section the sign is not necessary, which was magnitude representation removed | expressed as | x The result is called "note distance." FIG. 16A shows an example of a function of a temporal change of the “note distance” (hereinafter referred to as a note distance variation curve) obtained as described above, in which the vertical axis represents the “note distance” and the horizontal axis represents the “note distance”. Time. The section where the note distance variation curve is flat corresponds to the section where the pitch is stable.

When a note distance variation curve as shown in FIG. 16A is differentiated and a portion having a large falling or rising is defined as a break, two pitch stable sections PS1 and PS2 are detected. Although the pitch stable section may be obtained in this way, in this embodiment, the dynamic border curve is calculated, and the pitch stable section is detected based on the dynamic border curve. Here, the dynamic border curve is calculated based on the note distance variation curve. For example, the dynamic border at a certain sample point PX is an average value of the note distance variation curve from the start position to the sample point PX. And multiplying it by a predetermined constant. Note that an offset value may be added to this. FIG.
In the case of (A), the dynamic border curve becomes like a curve AC1. By comparing the dynamic border curve AC1 with the note distance variation curve NC1, a section where the note distance variation curve NC1 is smaller than the dynamic border curve AC1 is defined as a pitch stable section. At this time, when the dynamic border curve AC1 becomes smaller than the note distance variation curve NC1, the calculation of the dynamic border curve AC1 is stopped, and the value is kept to be maintained. When the held value becomes equal, the dynamic border curve AC1 up to the previous time is obtained.
Is reset, and the calculation of the dynamic border curve AC1 is started again from the beginning in the same manner. Thus, FIG.
This is shown in (B). Then, pitch stable sections PS3 and PS4 as shown in FIG. 16B are obtained.
In the case of the note distance variation curve NC1 as shown in FIG. 16, the pitch stable section detected by the differentiation processing and the pitch stable section detected by the dynamic border curve do not change much. However, in the case of the note distance variation curve NC2 as shown in FIG. 17, a clear difference appears.

In the case of the note distance variation curve NC2 shown in FIG. 17, the pitch is unstable in the latter half of the same vowel section. Pitch stable section PS5, PS
6, PS7, and PS8 appear in large numbers. However, in the case of the note distance variation curve of FIG. 17, the human ear responds dullly (sparsely) to a change in pitch in a portion where the pitch is unstable. The user does not feel a large number of stable pitch sections, but feels roughly two pitch stable sections as shown in FIG. On the other hand, if the pitch stable section is detected by the above-described dynamic border curve, it is possible to cause a reaction similar to that of the human ear. That is, when a dynamic border curve of the note distance variation curve NC2 in FIG. 17 is obtained, a curve AC2 as shown in FIG. 17B is obtained. Therefore,
The portion of the note distance variation curve NC2 smaller than the dynamic border curve AC2 becomes the pitch stable sections PS9 and PSA, and can be grasped as roughly two sections as shown in FIG. That is, a section in which the pitch is stable (FIG. 1)
In the 7 stable section PS9), when a certain pitch change occurs thereafter, the human feels that the sound division has changed, that is, a new sound has started. Conversely, in a section where the pitch is unstable (stable section PSA in FIG. 17), a slight change in the pitch is hardly perceived by the human ear,
It is not recognized as a new sound or section. Accordingly, in a section where the pitch is unstable, the change of the pitch is not recognized unless the change of the pitch is relatively large. In order to enable detection of such a pitch stable section close to the human ear, a dynamic section as described above is used as a curve, and a stable section or an unstable section is dynamically detected in a series of processes. We are doing the division. The stable pitch section detected in this way is a steady section finally detected by the steady section detection process in FIG. 5, that is, a section corresponding to one note when expressed as a musical score.

FIG. 6 is a diagram showing details of the pitch sequence determination processing in step 16 of FIG. The pitch sequence determination process is a process for determining an optimal pitch sequence for each stationary section detected in step 15. Hereinafter, the pitch sequence determination processing will be described with reference to FIGS. When voices, musical sounds, and the like are finally converted to note information, the melody greatly changes depending on the pitch to which a certain specific frequency is rounded, and in many cases, the desired detection cannot be performed. Therefore, in this embodiment, the pitch is determined mainly by the relative sound, and the pitch sequence is determined by selecting the most suitable pitch transition using the key. An example of this pitch sequence determination processing will be described with reference to the flowchart of FIG. Step 61: For each stationary section obtained by the stationary section detection processing of step 15 (FIG. 5), a representative frequency of the section is determined. FIG. 19A is a diagram illustrating an example of a finally obtained steady section. Here, it is assumed that a total of 12 sections have been detected, and each section is enclosed in parentheses.

Section numbers [0] to [12] are assigned.
What is important when determining the representative frequency of each stationary section is to identify the trend of the frequency from the periodic position of each stationary section and determine one unique frequency for that section. As a method for this, the first method uses the average frequency of the entire stationary section as the representative frequency of the section. In the second method, a cycle (frequency) near the middle of a stationary section is set as a representative frequency of the section. In the third method, the average frequency of the portion where the pitch is stable is set as the representative frequency of the section.
In this embodiment, the representative frequency is calculated using the note distance variation curve used in the subdivision processing based on the note distance in step 5D of FIG. 5 and the pitch stable section detected at that time. That is, step 5D in FIG.
The average value of the note distance variation curve in the section subdivided by the subdivision processing of, that is, the pitch stable section is obtained. This average value is used as a static border. For example, in the case of the note distance variation curve NC2 as shown in FIG. 17, the static border in the pitch section PS9 is SB1, and the static border in the pitch section PSA is SB2. And
The intervals in which the note distance variation curves NC2 in the pitch sections PS9 and PSA are smaller than the static borders SB1 and SB2 are defined as representative frequency detection sections F1 and F2, and the pitch of each waveform existing in the representative frequency detection sections F1 and F2 is Based on the steady section (pitch stable section) PS
9 and the representative frequency of the PSA are determined. For example, FIG.
The waveform section constituting the representative frequency detection section F1 of FIG.
(B), and the cycle length of each waveform section is as shown in the figure. In this case, the representative frequency detection section F
The average value of the cycle length at 1 is 255.833.
Here, the cycle length is represented by the number of samples,
Since the sampling frequency is 44.1 kHz, the representative frequency of the representative frequency detection section F1 can be obtained by dividing the sampling frequency by the average value of the period length. In the case of FIG. 19B, the representative frequency is 172.38 Hz. Become. In this case, the value of the representative frequency treats two decimal places as valid. FIG. 19C is a diagram showing a result of calculating the representative frequency of each steady section as shown in FIG. 19A.

Step 62: When the representative frequency of each stationary section is determined by the processing of step 61, the note distance between the consecutive section numbers before and after each stationary section is determined based on the representative frequency. The determination of the note distance is obtained in the same manner as the arithmetic expression used in step 5D of FIG. FIG. 19C shows an example of the note distance calculated as described above. Step 63: The calculated note distance is rounded off to one decimal place, and the note distance is rounded to each pitch on the 12th scale. For example, in the case of FIG. 19C, each note distance is rounded off and becomes an integer in the right column. Since this integer indicates the difference in note number from the previous pitch, it is possible to complete the pitch sequence data by determining the initial pitch. The pitch sequence data shown in the rightmost column of FIG. 19C is data indicating a state of a pitch transition when the first pitch is set to 0. That is, FIG.
In the case of (C), 0-2--4-5-2-3... Step 64: Determine the pitch of the first sound. First, the simplest method is to assign a 60 note number (note name C4) sound to the first sound as a default value. That is, in the case of the MIDI standard, the limit of the note number is 0 to 1
27, the note number 60
(Note name C4) is assigned. As a result, the pitch can be increased by 67 semitones on the high frequency side (plus side) and by 60 semitones on the low frequency side (minus side).
In this way, the data indicating the pitch sequence in the rightmost column in FIG. 19C is 60 (C4) -62 (D4) -64 (E4).
-65 (F4) -62 (D4) -63 (D♯4) ・ ・ ・
・ It becomes.

Step 65: The pitch sequence data determined in Step 64 is corrected. That is, the swing range of the pitch sequence data determined in step 64 is detected, and if it swings to -60 or less on the bass side (minus side), the default value 60 is set according to the minimum swing range. Fix it.
This correction is performed by shifting the default value upward so that the note with the minimum swing is 0 or more. For example, if the minimum swing width is −64, the calculation formula −60−
According to the result of (−64) = 4, the default value 60 is changed to 4
Shift up by a note and assign 64 as the first note. Even in the case where the swing is +67 or more on the treble side (plus side), the default value 60 may be similarly corrected in accordance with the maximum swing width. It is impossible to judge from the human utterance band that the swing width exceeds both the bass side (minus side) and the treble side (plus side), and such a case is excluded. If such a situation can occur, the range may be set in a range of 0 to 256. In step 64, the case where the pitch of the first sound is determined as a default value (for example, 60) and the pitch sequence data is created has been described. However, the present invention is not limited to this. It is also possible to detect the frequency of a close genuine scale and apply it to the scale. For example, in the case of FIG.

Since the representative frequency of [0] is 172.38 Hz, the pitch of the first sound is determined to be the note number 53 (note name F3) closest thereto. As a result, the data indicating the pitch sequence in FIG. 19C is 53 (F3) -55 (G3) -5
7 (A3) -58 (A♯3) -55 (G3) -56 (G
♯3) ... It goes without saying that the pitch sequence may be assigned by various other methods.

Next, the second case in which the electronic musical instrument according to the present invention operates as a sound signal analyzing device and a performance information generating device.
An embodiment will be described. The main flow when the electronic musical instrument according to the second embodiment operates as the sound signal analyzer and the performance information generator is the same as that in FIG.
The description is omitted. However, since the contents of each processing of steps 13 to 15 in the main flow are different from those of the first embodiment, the different points will be described in detail below.

FIG. 20 is a diagram showing details of the valid section detection processing in step 13 of FIG. 1, and corresponds to FIG. The valid section detection processing is processing for detecting a section in which a musical sound exists, that is, a valid section, based on the digital sample signal obtained as a result of the voice sampling processing in step 12. Hereinafter, the details of the valid section detection processing will be described with reference to FIG. Step 201: A process for dividing the digital sample signal obtained in step 12 into a predetermined number of samples is performed. FIG. 23A shows the sampling frequency 44.1.
FIG. 3 is a diagram illustrating an example of a waveform value of a voice signal sampled at kHz, that is, a digital sample signal. FIG.
(A) shows waveform values for about 4408 points. FIG. 23D shows a waveform value of about 8816 points which is twice as large. In step 201, a predetermined number of samples (for example, the lowest frequency of audio is set to 80 Hz
, The digital sample signal is divided by the number of samples corresponding to the maximum period). Therefore, when the sampling period is 44.1 kHz, the predetermined number of samples is “551 = 44100/80”. FIG.
(B) corresponds to the waveform values in FIG. 23 (A), and is a diagram showing a state of each waveform section S1 to S8 when the waveform values are divided every 551 samples.

Step 202: For each section divided by step 201, the maximum value of the digital sample signal waveform existing in that section is extracted. In FIG. 23 (C), the digital sample signal waveform of FIG. 23 (A) is indicated by a dotted line, and the maximum value of each waveform in each of the sections S1 to S8 is indicated by a black point. Step 203: Interpolate (for example, linearly interpolate) the maximum value of each section obtained in Step 202 to create an auxiliary waveform. FIG. 23D shows an auxiliary waveform corresponding to a section approximately twice as long as FIGS. 23A to 23C. The auxiliary waveform obtained by linearly interpolating the maximum value of each section is shown in FIG. Is shown. The waveform of the digital sample signal in FIG. 23A is shown by a dotted line. In the following steps 204 to 206, an effective section is extracted based on the auxiliary waveform thus obtained.

Step 204: The auxiliary waveform as shown in FIG. 23D obtained in step 203 is classified into an effective section and an invalid section based on a predetermined threshold Th. In this processing, the threshold Th is set to a value that is about one third of the maximum waveform value. It goes without saying that other values may be used as the threshold value Th. For example, the average value of the solid line waveform in FIG. 23D is set as the threshold value Th, or 80% of the average value is set as the threshold value T
h. Therefore, the intersection point between the threshold value Th and the auxiliary waveform is a boundary between the valid section and the invalid section, a section larger than the threshold Th is a valid section, and a section smaller than the threshold Th is a invalid section.

Step 205: If the minimum length required for human recognition of the pitch is 0.05 msec, an invalid section smaller than the minimum length is set as an effective section from the invalid sections determined in step 202. change. For example,
In the case where the sampling period is 44.1 kHz, the invalid period of 2205 or less in sampling number corresponds to the invalid period of 0.05 msec or less, which is the minimum length necessary for human being to recognize the pitch. Change the invalid section to a valid section. Since the invalid section in FIG. 23D is three waveform sections (about 1653 sampling numbers), it corresponds to an invalid section smaller than the minimum length. Is done. Step 206: As a result of the processing of the step 205, 0.0
A process of changing a short valid section of 5 msec or less to an invalid section is performed. This process is performed in the same manner as in the step 205.

FIG. 21 is a diagram showing details of the stable section detection processing in step 14 of FIG. 1, and corresponds to FIG. Hereinafter, with respect to the digital sampling signal in the effective section obtained by the effective section detection processing of FIG.
A stable section detection process for detecting a region with a stable level is performed. The operation of the stable section detection processing is shown in FIGS.
6 will be described. Step 211: Based on the digital sampling signal in the effective section detected by the effective section detection processing in FIG. 20, the side where the peak of the waveform appears strongly is detected. That is, as shown in FIG. 24A, the peak value max of the waveform on the plus (+) side and the peak value min of the waveform on the minus (−) side of the digital sampling signal within the effective section.
Are determined, and the side having the strongest peak is determined depending on which absolute value is larger. Note that a side having a strong peak may be determined by other methods. For example, the total of the absolute values of the top three to five peak values may be compared and determined. Step 212: On the side where the peak is detected in step 211, the envelope is taken forward (in the time lapse direction), and the peak portion is detected. That is, as shown in FIG. 24B, an envelope is taken ahead of the waveform on the plus side, and the peak portion is detected. As a result, in the case of FIG. 24B, four points P1 to P4 are detected as peak portions. Step 213: This time, the envelope is taken in the direction opposite to that of step 212 (the direction opposite to the elapsed time),
The peak part is detected. Then, as shown in FIG. 24C, peak portions P1 to P4 are detected at the same position, but other peak portions PP are detected depending on the waveform.
This means that in a waveform whose level is gradually rising, if the envelope is detected in only one direction, the overtone peak is mistaken as a pitch peak, and a portion that is not actually a peak (peak portion PP, etc.) ) May be erroneously detected as a peak. Therefore, as in steps 212 and 213, by detecting the peaks in different directions and detecting the peaks, the detection accuracy of the peaks can be improved.

Step 214: A new waveform is generated by linearly interpolating the peaks detected by the processing of steps 212 and 213. FIG. 24D shows a new peak value interpolation curve generated by linearly interpolating the peak portions P1 to P4 detected in steps 212 and 213. Note that FIG.
In (D), the digital sample signal waveform of FIG. 24 (A) is shown by a dotted line. Step 215: Calculate the total slope between the peaks based on the peak value interpolation curve generated by the above processing. In this process, as shown in FIG. 24D, the calculation width for calculating the inclination is, for example, 200 points, the shift amount of the calculation width is, for example, 100 points, and points corresponding to this shift amount are sequentially shifted. while doing,
The inclination is calculated. Assuming that the first sample point a1 of the valid section is “100”, the slope b1 between the sample points “100” and “300” is calculated by the following formula:
(A3-a1) / 200. Next, a slope b2 between sample points “200” and “400” obtained by shifting each point by 100 points is obtained.

FIG. 25 shows an example of the inclination calculated in this way. As is clear from the figure, the slope b1 between the sample points "100" and "300" is 0.03, the slope b2 between the sample points "200" and "400" is 0.15, and the sample points "300" and "300". The slope b3 between “500” is 0.25, and the sample point “400” −
The slope b4 between "600" is 0.50, the slope b5 between sample points "500" and "700" is 0.90, the slope b6 between sample points "600" and "800" is 1.80, and the sample point. The slope b7 between “700” and “900” is 1.90, and the sample point “800” −
The slope b8 between “1000” is 2.00, the slope b9 between sample points “900” and “1100” is 1.70,
The slope b10 between “1000” and “1200” is 1.2.
0, the inclination b11 between “1100” and “1300” is 0.
70. These slopes b1 to b11 are stored as the slopes at the former sample points a1 to a11. That is, the inclination b1 of the sample point a1 is 0.
03, assuming that the slope b2 of the sample point a2 is 0.15, the slope is stored for each sample point.

Next, the inclination b1 obtained in this way is
The total slope is determined based on the values of b11. The total slope is obtained by summing the last five slopes with reference to the sample point, and indicates the degree of the slope near the sample point. For example,
The total slope c1 of the sample point a1 is the slope b1 of the sample point a1 and the slope b four behind it.
It is calculated by summing 2 to b5. That is, it is calculated by c1 = b1 + b2 + b3 + b4 + b5. In the case of FIG. 25, the total slope c1 of the sample point a1 is 1.83, the total slope of the sample point a2 is 3.60, the total slope c3 of the sample point a3 is 5.35, and the total slope of the sample point a4 is 7 .1
0, the total slope of the sample point a5 is 8.30, the total slope c6 of the sample point a6 is 8.60, and the total slope of the sample point a7 is 7.50.

In this way, the total inclination in all sections is calculated, and the processing of the next step 216 is performed. Here, the case where the sum of the five points is set as the total slope at the beginning is described, but the present invention is not limited to this, and the total slope in the middle of the five points may be used. That is, the total slope c1 may be set to a value between the sample points a1 to a5, that is, the value of the sample point a3. In addition, if the position at five points is clear, the total inclination may be set to any value. Also, 5
It goes without saying that not only the points but also more or less may be used. By using the total inclination in this manner, an appropriate inclined portion can be found without being fooled by a temporary inclination, so that an appropriate stable portion can be found.

Step 216: A stable section is extracted this time based on the total slope calculated in step 215. That is, in a total slope curve formed by connecting the total slopes at each sample point by linear interpolation or other interpolation, a section having a predetermined value (for example, a total slope value of 5) or less is defined as a stable section, and other sections are defined as stable sections. Is an unstable section. Step 217: The maximum value of the waveform, that is, the maximum value of the peak value interpolation curve is detected for each section considered as a stable section by the processing of step 216, and if the maximum value is equal to or less than the predetermined value, the stable section is deleted. , Change to an unstable section. Step 218: Based on the existence of the stable section extracted in this way, the human first notices that there is a start point of the note trigger sound near the start point of the stable section.
Therefore, in order to determine the vicinity of the starting point of the note, the note starting point of the portion recognized as a stable section in steps 216 and 217 is detected, and the stable section is extended accordingly.

FIG. 26 shows steps 216 to 21.
8 illustrates the concept of processing up to 8. When the total slope curve in the effective section is as shown in FIG. 26, three stable sections d1 to d3 are detected by dividing the curve by a predetermined value. Note that the stable section d2 is deleted because the maximum value of the peak value interpolation curve is equal to or less than the predetermined value as a result of the process of step 217. Therefore, in the case of the effective section in FIG. 26, two stable sections d1 and d3 exist, and an unstable section including the deleted stable section d2 exists between the two stable sections d1 and d3. Will be. It is necessary to connect the unstable sections to the stable sections d1 and d3 and perform the extension processing of the respective stable sections d1 and d3.

As for the stable section d1, the start point of the effective section is necessarily the start point of the note in the stable section d1.
For the stable section d3, the final point of the effective section is necessarily the end point of the note in the stable section d3. The note start point of the stable section d3 and the end point of the stable section d1 are obtained as follows. That is, from the unstable sections detected in step 216, an unstable section that is closer to the stable section for which the note start point is to be detected is determined and corresponds to the peak value of the total slope curve in the unstable section. The sample point to be used is set as the note start point of the stable section. Therefore, when the stable section d2 is deleted and two unstable sections exist as shown in FIG. 26, the peak of the total slope is determined in the unstable section closer to the stable section d3 for which the note start point is to be detected. Sample point f corresponding to the value
2 is the note start point of the stable section d3. Accordingly, since the note end point of the stable section d1 is the sample point f2, the stable section d1 finally becomes the extended stable section e1, and the stable section d2 becomes the extended stable section e3. In the case of FIG. 26, if the stable section d2 is not deleted in the process of step 217, the sample point f1 becomes the note end point of the stable section d1 and the note start point of the stable section d2, and the sample point f2 becomes This is the note end point of the stable section d2 and the note start point of the stable section d3.

FIG. 22 is a diagram showing details of the stationary section detection processing in step 15 of FIG. 1 and corresponds to FIG. How the steady section is detected from the stable sections obtained by the stable section detection processing of FIG. 21 will be described in detail. Steps 221 and 2 in the stationary section processing of FIG.
Since step 29 is almost the same as steps 51 to 59 shown in FIG.

Step 221: Pass a first-order band-pass filter (first-order BPF) to delete predetermined harmonics. Step 222: A peak reference position detection process, which is a reference for one cycle, is performed on the musical tone waveform signal obtained by the primary BPF process of step 221 using a peak position detection method. Step 223: Based on the peak reference position detected in step 222, a basic section starting from a certain peak reference position and a section up to the next peak reference position immediately after the basic section (hereinafter referred to as a moving section). FIG. 1 shows a comparison of whether or not the waveforms of two sections between
This is performed by an error rate calculation method as shown in FIG. Step 224: Using the result of the waveform comparison process of step 223, the sections in which the error rate is smaller than a predetermined value (for example, 10) are connected to each other to be a pseudo matching section, and extracted from each matching section. The maximum value and the minimum value of the pitch are detected, and the cutoff frequency band is determined based on the maximum value and the minimum value. Step 225: Using the new cut-off frequency band determined in Step 224, pass through a second-order band-pass filter (second-order BPF) to remove unnecessary harmonics. Step 226: The same processing as the peak reference position detection processing of step 222 is performed. Step 227: The same processing as the waveform comparison processing of step 223 is performed. By a series of processes from step 225 to step 227, low frequencies and harmonics that cause errors are cut, and more accurate peak reference position detection processing and waveform comparison processing can be performed. A matching section is obtained. Step 228: The pitch data at each peak reference position obtained by the processing up to step 227 is interpolated, and linear interpolation is performed so that one pitch data is obtained for each sample point.

Step 229: A time-varying band-pass filter (BPF) process is performed using the pitch data for each sample point obtained by the process of step 228. Step 22A: For the musical sound waveform that has undergone the time-varying band-pass filter processing in step 229, determine the side where the peak is strong, and determine the musical sound waveform according to the period interval determined based on the frequency change obtained in step 228. , And the maximum position in each section is detected, and this is set as the peak reference position. That is, when the tone waveform obtained by the time-varying band-pass filter processing in step 229 is as shown in FIG. 27, the period sections PR1 to PR1 determined based on the frequency change are used.
Each tone waveform is separated by PR5. The maximum values P1 to P6 in the divided sections PR1 to PR5 are peak reference positions. When the peak reference position is detected by the peak reference position detection processing as in step 222 (step 52) or step 226 (step 56), FIG.
In the case of the waveform shown in (A), there is a problem that the peak reference positions P4 and P5 appear at erroneously wrong positions. However, as in step 22A, the musical tone waveform is divided by a period section, and In the case where the peak reference position is detected by such a method, such a clearly incorrect peak reference position is not detected, and the accuracy of peak reference position detection is improved.

Step 22B: A voiced section detection process of the waveform is performed based on the peak reference position detected by the peak reference position detection process of step 22A. That is, in this voiced section detection process, as in step 223, based on the peak reference position detected in step 22A,
Whether the waveforms of two sections between a basic section starting from a certain peak reference position and a section immediately after the basic section to the next peak reference position (hereinafter referred to as a moving section) are the same. Are performed by an error rate calculation method as shown in FIG. Therefore, in this voiced section detection process, if it is determined that the basic section and the moving section do not match, the section is not immediately delimited as a voiced section. And a delimiter. This makes it possible to detect a "vowel continuous portion", such as "a-a-a-" or "a-a-a-", as a voiced section.

For example, in the case of FIG.
Assuming that a section from 1 to the peak reference position P2 is a basic section P12, a section from the peak reference position P2 to the peak reference position P3 is a movement section P23. In this case, it is assumed that it is determined that the basic section P12 and the moving section 23 match. Section P23
And section P34 are also determined to be the same. When it is determined that the next section P34 and the section P45 do not match, the section P34 and the section P56 next to the section P45 are determined.
And performs a waveform comparison process. As a result, when it is determined that the section P34 and the section P56 match, the section P34 and the section P4 are set even if the section P45 and the section 56 do not match.
5. The section P56 is determined to be the same, and the process proceeds to the next section P56 and section P67 (not shown). At this time, section P34 and section P45, section P34 and section P56, section P
34 and section P67 (not shown), section P34 and section P7
8 (not shown), section P34 and section P89 (not shown)
Are determined as non-coincidences, that is, when the non-coincidence occurs continuously for a predetermined number of times (for example, 5 times) or more, the section P34 is set as a section of the voiced section, and the same determination is performed for the next section P45 and the section P56. I do. Section P
If the interval 45 and the interval P56 do not match, a determination is made for the interval P45 and the interval P67 (not shown). When the section 45 and the section P56 do not match, the process of determining whether the mismatch continues is not performed, and the next section P56 and the section P6 are not performed.
7 may be determined, and the same matching process as described above may be performed only when adjacent sections match. When the voiced section is determined in this way, the voiced section having a predetermined length or less (short voiced section) is deleted.

By the above processing, the stable section is set as shown in FIG.
Voiced section V separated by unstable section as shown in
They are classified as 1 to V3. This voiced section V1
ＶV3 corresponds to a stable portion having a low value of the adjacent comparison error curve, and a portion having a high value of the adjacent comparison error curve corresponds to the unstable section. Therefore, expansion processing of the stable sections V1 to V3 is performed based on this adjacent comparison error curve. This expansion process unconditionally extends the effective section adjacent to the start point and end point of the stable section to the start point and end point of the stable section, and performs adjacent comparison for the unstable section between two voiced sections. The effective section is extended using the maximum value of the error as a breakpoint. Therefore, in the case of the adjacent comparison error curve as shown in FIG. 29, each voiced section V1 to V3 becomes an expanded voiced section V1E to V3E by the expansion processing. In addition,
In FIG. 29, the slope of the adjacent comparison error in the extended voiced section is 0
Although only one portion (base portion) is shown, it is needless to say that there may be a plurality of portions (bottom portion) where the inclination of the adjacent comparison error is 0 in actuality. .

Step 22C: With respect to each extended voiced section obtained by the processing from step 221 to step 22B, a part (base part) where the error of the adjacent section, that is, the slope of the adjacent comparison error becomes 0, is detected. A process for detecting a section corresponding to the pronunciation of the vowel as a timbre section is performed as a reference position of the vowel. In the processing for detecting the tone color section, a waveform section corresponding to the base portion is fixed as a basic section, and a plurality of waveform sections existing before and after the section are set as moving sections, and a waveform comparison process is sequentially performed to obtain a comparison error. The comparison error thus obtained is called a reference comparison error. That is, as shown in FIG. 30A, a waveform section m0 corresponding to the bottom portion of the adjacent comparison error is set as a basic section, and this basic section and a plurality of moving sections m1,
m-1, m2, m-2, m3, m-3, m4, m-4
Performs waveform comparison processing with. The basic section is a section corresponding to the lowest value of the adjacent comparison error, that is, a waveform section determined as having high coincidence as a result of the waveform comparison processing. The comparison error thus obtained becomes a reference comparison error curve as shown in FIG. This reference comparison error curve shows the same tendency as the adjacent comparison error curve in the vicinity of the waveform section m0 due to the waveform comparison processing performed on the basis of the waveform section m0. Increases and converges to the maximum error rate. The waveform section in which the value (error rate) of the reference comparison error curve is equal to or less than a predetermined value is the timbre section TS1. When the reference comparison error curve is obtained, as in the voiced section detection process in step 22B, if the value of the reference comparison error curve becomes larger than a predetermined value, the reference comparison error curve is not immediately used as a delimiter of the timbre section. When a value larger than a predetermined value occurs continuously for a predetermined number of times or more, it is defined as a timbre section break.

When the timbre section is determined in this way, if the length of the undecided section other than this timbre section is longer than a predetermined length in the extended voiced section, the same applies to the extended speech section other than the determined timbre section. Perform processing. That is, FIG.
In the case of, when the timbre section TS1 as shown in FIG. 30B is determined, the extended voiced section other than this timbre section TS1, that is, the undecided section length is equal to or longer than a predetermined length. A waveform section n0 corresponding to the base portion of the adjacent comparison error as shown in FIG. 30C is set as a basic section, and the basic section and a plurality of moving sections n1, n-1, n2, n- 2, n3, n-3, n4
Perform waveform comparison processing with n-4. The comparison error obtained in this manner becomes a reference comparison error curve as shown in FIG. Value of this reference comparison error curve (error rate)
Is below the predetermined value, this time the timbre section TS2
Becomes Therefore, in the case of the extended voiced section in FIG. 30, two tone color sections TS1 and TS2 are detected.

Step 22D: The timbre section obtained by the processing of step 22C is extended in the same manner as the stationary section extension processing of step 5C. That is, step 2
As a result of performing the processing from step 21 to step 22C, if the detected timbre section ST1 and speech section ST2 are separated by one waveform section, the waveform section is directly changed to the timbre sections ST1 and ST2. It is sufficient to set a delimiter. However, when adjacent timbre sections are separated by a plurality of waveform sections, these timbre sections must be connected to the preceding and following timbre sections to extend the timbre section. The process of expanding the tone color section is performed by the same process as in FIG. In this case as well, since the comparison process is performed on a waveform close to the sine waveform after the BPF process, even the features of each vowel are filtered, and the significance of extracting the same vowel section, that is, the same timbre, is diminished. There is a risk that it will. Therefore, a waveform for peak position detection and a waveform for waveform comparison processing may be separately prepared, and the peak position detection and waveform comparison processing may be respectively performed based on the waveforms. That is, the waveform after the time-varying BPF processing is used as it is as the waveform for peak position detection, and the BPF processing for leaving a frequency band waveform several times as long as the frequency component used in the time-varying BPF processing is used for the waveform comparison processing. The waveform obtained by performing the above is used. It goes without saying that band-pass filter processing may be performed in which the basic frequency is set to the lowest frequency and the integral frequency of the basic frequency is set to the highest frequency, and this may be used as a target waveform for the waveform comparison processing.

The subdivision process is performed on the expanded tone color section in consideration of the change in pitch and stability, and the final pitch section is determined. In the timbre section detection processing up to step 22C, since the waveform is expanded and compared, even if the pitch change of the voice waveform is caused by a continuous vowel such as "Oh", it is regarded as one and the same sound. It is a mechanism. Therefore, in the case of the musical sound waveform of the musical instrument sound, a situation may occur in which the pitch change of the continuous musical instrument sound cannot be found. Therefore, in this embodiment, the state of the pitch change is examined for each timbre section obtained by the processing up to step 22C, and it is determined whether further division is necessary according to the state. If it is determined that it is necessary, the timbre section is divided into smaller pitch sections. The process of dividing the timbre section into pitch sections is performed using a note distance variation curve as shown in FIG.

Step 22E: The interval detected by the process of step 22D may include a note that is too short to exist as a note.
Therefore, in this step, one bar is equally divided into a grid in units of a predetermined note length (for example, eighth note length), and the pitch interval is applied to this grid to determine a note value. . The interval section is assigned to the grid closest to the beginning of each interval section.
If two or more intervals are closest to one grid, the longer interval of those intervals is applied to the grid. For example, FIG.
1 is a diagram showing an example of a musical interval corresponding to one measure divided by an eighth note length. In the figure, step 22D
The pitch interval finally determined by PT1 to PT5
Let's say In this case, the interval PT1 applies to the grid G2, the interval PT2 applies to the grid G4, and the interval PT3 applies to the grid G5. However, with regard to the grid G6, the interval PT4 and the interval PT5 are the intervals closest to the grid G6. Therefore, in this case, the longer interval between the interval PT4 and the interval PT5, that is, the interval PT5 is applied to the Grigg G6. Note that, since the pitch section PT3 is applied to the grid G5, the pitch length of the pitch section PT2 is from the grid G4 to the grid G5. The final position of the pitch of PT2 may be used as it is, or the interval of the interval PT2 may be applied to the nearest grid. In this case, note-off (rest) may be applied to a portion where no interval exists. When the interval PT3 does not exist, the last position of the pitch of the interval PT2 may be set to the grid G6, which is the start position of the next interval PT5. In this case, note-off (rest) does not exist. After the pitch value is determined by the stationary section detection process of FIG. 22 in this way, the optimum pitch sequence is assigned to each pitch value by the pitch sequence determination process of step 16 of FIG. This pitch sequence determination processing is the same as that of the first embodiment, and thus the description is omitted.

[0096]

According to the sound signal analyzing apparatus of the present invention, even when the pitch or level of the input sound from the microphone or the like slightly fluctuates, the stationary part of the musical sound other than the fluctuated part, that is, 1 A sound signal analyzer capable of analyzing a portion corresponding to one note can be provided.

[Brief description of the drawings]

FIG. 1 is a diagram showing a main flow when the electronic musical instrument of FIG. 2 operates as a performance information generating device.

FIG. 2 is a hardware block diagram showing a configuration of an electronic musical instrument incorporating a musical sound information analyzer and a performance information generator according to the present invention.

FIG. 3 is a diagram showing details of an effective section detection process in step 13 of FIG. 1;

FIG. 4 is a diagram showing details of a stable section detection process in step 14 of FIG. 1;

FIG. 5 is a diagram showing details of a stationary section detection process in step 15 of FIG. 1;

FIG. 6 is a diagram showing details of a pitch sequence determination process in step 16 of FIG. 1;

FIG. 7 is a diagram illustrating an example of a waveform value of an audio signal sampled at a sampling frequency of 44.1 kHz, that is, a digital sample signal.

FIG. 8 is a diagram showing a concept of an operation example of the valid section detection processing of FIG. 3;

9 is a diagram showing a concept of an operation example of the stable section detection processing of FIG.

10 is a diagram showing a concept of an operation example by the first and second order BPF processes and the waveform comparison process of FIG. 5;

11 is a diagram showing a waveform example when a strong peak of a musical tone waveform in a stable section appears on the minus side and a weak peak appears on the plus side after the first-order BPF processing in step 51 of FIG.

FIG. 12 shows a specific example of how the calculation method of the error rate performed in the waveform comparison processing of FIG. 5 is performed.
FIG. 5 is a diagram illustrating the comparison waves.

FIG. 13 shows the waveform comparison process shown in FIG.
It is a figure which shows the concrete numerical value how the error rate is calculated from this comparison wave.

FIG. 14 is a diagram showing a specific example of how a peak reference position is extracted by the peak reference position detection processing in FIG. 5 when the time constant is set to be small.

FIG. 15 is a diagram illustrating an operation example of a steady section extension process in step 5C of FIG. 5;

FIG. 16 is a diagram illustrating an operation example of a subdivision process based on a note distance in step 5D of FIG. 5;

FIG. 17 is a diagram illustrating another operation example of the subdivision processing based on the note distance in step 5D of FIG. 5;

FIG. 18 is a diagram illustrating an example of an operation of determining a representative frequency from which part of the steady section to detect a representative frequency when performing the representative frequency determination processing of each steady section in step 61 of FIG. 6;

FIG. 19 is a diagram showing an operation example of how a representative frequency is detected from each stationary section in step 61 of FIG. 6;

FIG. 20 is a diagram showing details of an effective section detection process in step 13 of FIG. 1 according to another embodiment.

FIG. 21 is a diagram showing details of a stable section detection process according to another embodiment in step S14 of FIG. 1;

FIG. 22 is a diagram illustrating details of another embodiment of the stationary section detection processing in step 15 of FIG. 1;

FIG. 23 is a diagram showing a concept of an operation example of the valid section detection processing of FIG. 20;

FIG. 24 shows steps 211 to 21 of FIG.
It is a figure which shows the concept of the operation example of the process to 5.

FIG. 25 is a diagram illustrating an example of calculating a total inclination in step 215 of FIG. 21.

FIG. 26 shows steps 216 and 21 of FIG.
8 is a diagram illustrating a concept of an operation example of the processing of No. 8; FIG.

FIG. 27 is a diagram showing a concept of an operation example of the peak reference position detection processing in step 22A of FIG. 22.

FIG. 28 is a diagram showing the first half of the concept of an operation example in the voiced section detection processing in step 22B of FIG. 22;

FIG. 29 is a diagram illustrating the latter half of the concept of the operation example in the voiced section detection process in step 22B of FIG. 22;

30 is a diagram showing a concept of an operation example in the tone color section detection processing in step 22C of FIG. 22.

FIG. 31 is a diagram showing a concept of an operation example in a tone value determination process in step 22E of FIG. 22.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... CPU, 2 ... program memory, 3 ... working memory, 4 ... performance data memory, 5 ... key press detection circuit, 6 ...
Microphone interface, 7 ... Switch detection circuit, 8 ...
Display circuit, 9: sound source circuit, 10: keyboard, 1A: microphone, 1B: numeric keypad and various switches, 1C: display, 1D: sound system, 1E: data and address bus

Claims (39)

[Claims] An input means for inputting an arbitrary sound signal, and an average value over a predetermined number of samples of a sample amplitude value of the sound signal input from the input means is obtained. Calculating means for outputting as level information; first section detecting means for detecting a first section in which a musical sound is considered to be present from the sound signal based on the average level information obtained by the calculating means; And a second section detecting means for detecting a second section for sound signal analysis from the first section based on a sample amplitude value of the sound signal in the first section. Characteristic sound signal analyzer. 2. An input means for inputting an arbitrary sound signal, detecting a maximum value of a sample amplitude value of the sound signal input from the input means for each predetermined number of samples, and detecting the detected maximum value. A waveform creating unit that creates an auxiliary waveform by interpolating; and a first section that detects a first section in which a musical sound is considered to exist from the sound signal based on the auxiliary waveform created by the waveform creating unit. One section detecting means; and second section detecting means for detecting a second section for sound signal analysis from the first section based on a sample amplitude value of the sound signal in the first section. A sound signal analyzer comprising: 3. An input means for inputting an arbitrary sound signal, a filter means for performing a filtering process of a predetermined frequency characteristic on the sound signal, and a continuous sample amplitude value in the filtered sound signal. Analyzing means for analyzing the degree of coincidence between adjacent waveforms, and detecting, as the same waveform section, a section composed of a plurality of continuous waveforms analyzed by the analyzing means as matching within a range according to a predetermined condition. A sound signal analyzing apparatus comprising: a section detecting means; and a pitch detecting means for detecting a pitch of the sound signal in the same waveform section detected by the section detecting means. 4. An input means for inputting an arbitrary sound signal, and a pitch of the sound signal is detected for each predetermined section with respect to the sound signal input from the input means, and a data string of the detected pitch is generated. First pitch detection means for performing filtering processing for variably controlling a pass band in accordance with a frequency corresponding to each pitch in the pitch data string to the input sound signal; A second pitch detecting means for detecting a more accurate pitch of the sound signal based on a sample amplitude value of the sound signal output from the means. 5. An input means for inputting an arbitrary sound signal, and detecting a pitch of the sound signal at predetermined intervals with respect to the sound signal input from the input means, and generating a data string of the detected pitch. First pitch detection means for performing filtering processing for variably controlling a pass band in accordance with a frequency corresponding to each pitch in the pitch data string to the input sound signal; Analysis means for analyzing the degree of coincidence between adjacent waveforms based on successive sample amplitude values in the subsequent sound signal; and a plurality of continuous waveforms analyzed by the analysis means to be consistent within a range according to a predetermined condition. Section detection means for detecting a section having the same waveform as the same waveform section; and the sound signal in the same waveform section detected by the section detection means. The sound signal analysis device, characterized in that it comprises a second pitch detecting means for detecting a pitch. 6. An input means for inputting an arbitrary sound signal, and detecting a pitch of the sound signal for each predetermined section with respect to the sound signal input from the input means, and generating a data string of the detected pitch. A first pitch detecting means, and a filtering process in which a pass band is time-varying controlled in accordance with a frequency corresponding to each pitch in the pitch data sequence,
Filter processing means for applying to the input sound signal; analysis means for analyzing the degree of coincidence between adjacent waveforms based on continuous sample amplitude values in the sound signal after the filter processing; and First section detection means for detecting a first section consisting of a plurality of continuous waveforms analyzed to be identical within a range according to a condition; and a first section detected by the first section detection means. A second section detection means for determining a degree of coincidence between a plurality of waveforms before and after the waveform having a higher degree of coincidence as a reference and detecting a second section having a higher degree of coincidence; And a second pitch detecting means for detecting a pitch of the sound signal in a second section detected by the means. 7. An input means for inputting an arbitrary sound signal, and a first filter for performing a band-pass filter process for setting a predetermined cut-off frequency to a maximum frequency and a minimum frequency on the sound signal input from the input means. Processing means; first cycle reference detection means for detecting a plurality of first candidate positions serving as a cycle reference for the sound signal output from the first filter processing means; detection by the first cycle reference detection means Said first
A frequency band detecting means for detecting a maximum frequency and a minimum frequency of the sound signal based on the candidate position; and a band filter process for setting the maximum frequency and the minimum frequency detected by the frequency band detecting means to a cutoff frequency. Second filter processing means for applying the sound signal input from the means, and second cycle reference detection means for detecting a plurality of candidate positions serving as a cycle reference for the sound signal output from the second filter processing means. A sound signal analyzing apparatus comprising: a pitch detecting means for detecting a pitch of the sound signal for each of the candidate positions detected by the second cycle reference detecting means. 8. An input means for inputting an arbitrary sound signal, a filter means for filtering the sound signal in a predetermined frequency band, and a peak position of the sound signal after the filtering processing by the filter means. A peak position detecting means for detecting each of the peak positions, and a limit by a pass band of the filter among various sections obtained by dividing the waveform of the sound signal between any two peak positions detected by the peak position detecting means. For a section having a time length corresponding to the above, two pairs of adjacent sections are selected as many as possible, and the degree of coincidence of the waveforms of the two sections in each selected pair is determined. A section detecting means for detecting a pair as the same waveform section; and a stationary section for sound signal analysis based on the same waveform section detected by the section detecting means. The sound signal analysis device, characterized in that it comprises a stationary section detecting means for output. 9. An input means for inputting an arbitrary sound signal, a peak position detecting means for detecting a peak position of the input sound signal, and an arbitrary two signals detected by the peak position detecting means. Among various sections obtained by dividing the waveform of the sound signal between the peak positions, the degree of coincidence between the waveforms of any two adjacent sections is determined, and the sections having a high degree of coincidence are connected to each other to determine the degree of coincidence. A first section detecting means for detecting one of the same waveform section groups; and a start section and a last section in the first same waveform section group as comparison target sections before and after the first same waveform section group. A degree of coincidence of waveforms is calculated for each of the adjacent sections, and the first same waveform section group is extended before and after that based on the calculated degree of coincidence, and this is detected as a second same waveform section group. Two section detection means, A sound signal analyzing apparatus, comprising: a stationary section detecting means for detecting a stationary section for sound signal analysis based on the second group of the same waveform sections detected by the second section detecting means. 10. An input means for inputting an arbitrary sound signal, and a pitch of the sound signal is detected for each predetermined section with respect to the sound signal input from the input means, and a data sequence of the detected pitch is generated. Pitch detecting means, and a relative value converting means for converting a difference between successive pitches in the pitch data string into relative values based on a cent value of a pitch, and a relative value obtained by the relative value converting means. Based on a dynamic average, a dynamic reference calculation means for calculating a dynamic reference value, and a relative value obtained by the relative value conversion means and a dynamic reference value calculated by the dynamic reference calculation means A sound signal analyzer comprising: a stationary section detecting means for detecting a stationary section for sound signal analysis in comparison. 11. The apparatus further comprises note analysis means for analyzing a pitch of the sound signal and determining a note of the sound signal in the second section or the stationary section for analyzing the detected sound signal. 10. The method according to claim 1, wherein:
11. The sound signal analyzer according to any one of claims 10 and 10. 12. An input means for inputting an arbitrary sound signal, and detecting a pitch of the sound signal for each predetermined section with respect to the sound signal input from the input means, and generating a data string of the detected pitch. Pitch detection means, and a filtering process in which the pass band is time-varying controlled according to the frequency corresponding to each pitch in the pitch data sequence,
First filter processing means for applying the input sound signal, cycle reference position detection means for detecting a plurality of candidate positions serving as a cycle reference for the sound signal output from the first filter processing means, and the pitch data Second filter processing means for performing a filtering process in which a pass band is subjected to time-varying control in accordance with a frequency corresponding to each pitch in the row and a frequency that is a predetermined integer multiple thereof, to the input sound signal; Section detection for determining the degree of coincidence of waveforms in a plurality of sections obtained by dividing the sound signal output from the second filter processing means in accordance with a position, and detecting a section having a high degree of coincidence as the same waveform section Means, and pitch analysis means for analyzing the pitch of the sound signal based on the same waveform section detected by the section detection means. Sound signal analyzer. 13. A providing means for providing a continuous sample amplitude value of an arbitrary sound signal, and a first filter processing means for performing a first filtering process of a predetermined characteristic on the provided continuous sample amplitude value. Control data creating means for creating control frequency data for second filtering based on the continuous sample amplitude values subjected to the first filtering; characteristics based on the created control frequency data Second filter processing means for performing the second filter processing on the continuous sample amplitude values provided by the providing means, and based on the continuous sample amplitude values subjected to the second filter processing. And a pitch detecting means for detecting a pitch of the sound signal. 14. An input means for inputting an arbitrary sound signal, and a pitch of the sound signal is detected for each predetermined section with respect to the sound signal input from the input means, and a data string of the detected pitch is generated. Pitch detecting means, and a relative value converting means for converting a difference between successive pitches in the pitch data string into relative values based on a cent value of a pitch, and a relative value obtained by the relative value converting means. Based on a dynamic average, a dynamic reference calculation means for calculating a dynamic reference value, and a relative value obtained by the relative value conversion means and a dynamic reference value calculated by the dynamic reference calculation means A stationary section determining means for comparing and detecting a stationary section for pitch analysis; and a static reference calculating means for calculating a static reference value based on a static average of the relative values in the stationary section. Comparing the static reference value and the relative value in the stationary section, a pitch determining section detecting means for detecting a pitch determining section for calculating a representative frequency of the stationary section, And a frequency calculating means for calculating a representative frequency of the stationary section based on the pitch data sequence in the pitch determining section. 15. An input means for inputting an arbitrary sound signal composed of a time series of one or a plurality of notes, and it is presumed that each of the input sound signals corresponds to each note. A section detecting means for detecting each section; and arranging the detected sections on a grid divided at a time interval corresponding to a predetermined note length in accordance with the time series, and starting or ending the end of each steady section. One of the grid positions closest to one of the predetermined ends is assigned to each stationary section, and as a result, if a plurality of stationary sections are assigned to the same grid position, one stationary section having the longest time length is assigned. Means for selecting a section as a valid note. 16. A step of inputting a sound signal to be analyzed, and a step of obtaining an average value of sample amplitude values of the input sound signal over a predetermined number of samples, and outputting the result as time-series average level information. Detecting a first section in which a musical sound is considered to be present from the sound signal based on the average level information; based on a sample amplitude value of the sound signal in the first section Detecting a second section for analyzing the sound signal from the first section. 17. An auxiliary waveform by inputting a sound signal to be analyzed, detecting a maximum value of a sample amplitude value of the input sound signal for each predetermined number of samples, and interpolating the detected maximum value. And detecting a first section where a musical sound is considered to be present from the sound signal based on the generated auxiliary waveform; and the sound signal in the first section. Detecting a second section for analyzing the sound signal from the first section based on the sample amplitude value of the first section. 18. A step of inputting a sound signal to be analyzed, a step of performing a filtering process with a predetermined frequency characteristic on the input sound signal, and a continuous sample amplitude value in the filtered sound signal. Analyzing the degree of coincidence between adjacent waveforms on the basis of the above, and detecting, as the same waveform section, a section composed of a plurality of continuous waveforms that have been analyzed as matching within a range according to a predetermined condition by the step. A method for analyzing a sound signal, comprising the steps of: detecting a pitch of the sound signal in the detected same waveform section. 19. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal in each of predetermined intervals with respect to the input sound signal, and generating a data string of the detected pitch. Performing a filtering process in which a pass band is variably controlled in accordance with a frequency corresponding to each pitch in the pitch data sequence, to the input sound signal, based on a sample amplitude value of the filtered sound signal. Detecting a more accurate pitch of the sound signal. 20. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal for each of predetermined intervals with respect to the input sound signal, and generating a data sequence of the detected pitch. Performing a filtering process in which a pass band is variably controlled in accordance with a frequency corresponding to each pitch in the pitch data sequence to the input sound signal, based on a continuous sample amplitude value in the filtered sound signal Analyzing the degree of coincidence between adjacent waveforms, and detecting, as the same waveform section, a section composed of a plurality of continuous waveforms that have been analyzed to be matched within a range according to a predetermined condition by the step. Detecting the pitch of the sound signal in the detected same waveform section. Method. 21. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal in each of predetermined intervals with respect to the input sound signal, and generating a data string of the detected pitch. Filter processing in which the pass band is time-varying controlled according to the frequency corresponding to each pitch in the pitch data sequence,
Applying to the input sound signal; analyzing the degree of coincidence between adjacent waveforms based on continuous sample amplitude values in the filtered sound signal; and Detecting a first section consisting of a plurality of continuous waveforms that have been analyzed as being coincident with each other; and determining a plurality of waveforms before and after the detected waveform having a higher degree of coincidence in the first section. Determining a degree of coincidence between each waveform and detecting a second section having a higher degree of coincidence; and detecting a pitch of the sound signal in the detected second section. A method for analyzing a signal. 22. A step of inputting a sound signal to be analyzed, a step of filtering the input sound signal in a predetermined frequency band, and detecting a peak position of the sound signal after the filtering processing. And, among various sections obtained by dividing the waveform of the sound signal between any two of the detected peak positions,
For a section having a time length commensurate with the restriction by the pass band of the filter, two pairs of adjacent sections are selected as many as possible, and the degree of coincidence of the waveforms of the two sections in each selected pair is determined. Detecting a pair having the highest degree of coincidence as the same waveform section; and detecting a stationary section for sound signal analysis based on the detected same waveform section. Method. 23. A step of inputting a sound signal to be analyzed, a step of detecting a peak position of the input sound signal, and a step of dividing a waveform of the sound signal between any two peak positions. Of any two adjacent sections
Determining the degree of coincidence of the waveforms of the two sections, connecting the sections having a high degree of coincidence to detect a first same-waveform section group, and determining a start section in the first same-waveform section group. Using the last section as a comparison target section, the degree of coincidence of the waveform is calculated for each of the sections adjacent before and after the first same waveform section group, and based on the calculated degree of match, the first same waveform section group is calculated. And a step of detecting this as a second group of the same waveform sections, and a step of detecting a steady section for sound signal analysis based on the detected second group of the same waveform sections. A method for analyzing a sound signal to be played. 24. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal for each of predetermined intervals with respect to the input sound signal, and generating a data string of the detected pitch. Applying a first filter process in which a pass band is time-varying controlled in accordance with a frequency corresponding to each pitch in a pitch data sequence to the input sound signal; and a sound subjected to the first filter process. Detecting a plurality of candidate positions serving as a cycle reference for the signal; and a second filter process in which a pass band is time-varying controlled according to a frequency corresponding to each pitch in the pitch data string and a frequency of a predetermined integer multiple thereof. To the input sound signal, and classifying the sound signal that has been subjected to the second filter processing in correspondence with each of the detected candidate positions. Determining the degree of coincidence of the waveforms of a plurality of sections obtained by performing the above, detecting a section having a high degree of coincidence as the same waveform section, and analyzing a pitch of the sound signal based on the detected same waveform section. And a step for analyzing the sound signal. 25. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal for each of predetermined intervals with respect to the input sound signal, and generating a data string of the detected pitch. Converting a difference between successive pitches in the pitch data sequence into relative values based on a cent value of a pitch; and calculating a dynamic reference value based on a dynamic average of the converted relative values. Step, comparing the converted relative value and the dynamic reference value,
Detecting a stationary interval for analyzing the sound signal. 26. providing a continuous sample amplitude value of an arbitrary sound signal; applying a first filter processing of a predetermined characteristic to the provided continuous sample amplitude value; Generating control frequency data for a second filter process based on the continuous sample amplitude values subjected to the filter process; and a second filter process having characteristics based on the generated control frequency data, Applying a sound to the continuous sample amplitude value provided; and detecting a pitch of the sound signal based on the continuous sample amplitude value subjected to the second filtering. A method for analyzing a signal. 27. A step of inputting a sound signal to be analyzed, a step of detecting a pitch of the sound signal for each of predetermined intervals with respect to the input sound signal, and generating a data sequence of the detected pitch. Converting a difference between successive pitches in the pitch data sequence into relative values based on a cent value of a pitch; and calculating a dynamic reference value based on a dynamic average of the converted relative values. Step, comparing the converted relative value and the dynamic reference value,
Detecting a stable stationary section for pitch analysis; calculating a static reference value based on a static average of the relative values within the stationary section; and the static reference value and the stationary section Comparing the relative value within the interval, detecting a pitch determination section for calculating the representative frequency of the stationary section, and based on the pitch data string in the detected pitch determination section Calculating a representative frequency of the stationary section. 28. A recording medium readable by a machine, comprising, as its storage contents, a group of instructions for a program for analyzing a sound signal executed by a computer, and for analyzing the sound signal. The program includes a step of inputting a sound signal to be analyzed, a step of obtaining an average value of a sample amplitude value of the input sound signal over a predetermined number of samples, and a step of outputting the result as time-series average level information. Detecting a first section in which a musical sound is considered to be present from the sound signal based on the average level information; and based on a sample amplitude value of the sound signal in the first section. Detecting a second section for sound signal analysis from the first section. 29. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. The program includes a step of inputting a sound signal to be analyzed, detecting a maximum value of a sample amplitude value of the input sound signal for each predetermined number of samples, and interpolating the detected maximum value to generate an auxiliary waveform. Creating; detecting a first section in which a musical sound is considered to be present from the sound signal based on the created auxiliary waveform; and detecting the first section of the sound signal in the first section. Detecting a second section for sound signal analysis from the first section based on the sample amplitude value. 30. A recording medium readable by a machine, having, as its storage contents, a group of instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A step of inputting a sound signal to be analyzed; a step of performing a filter process of a predetermined frequency characteristic on the input sound signal; and a step of applying a continuous sample amplitude value in the sound signal after the filter process. Analyzing the degree of coincidence between adjacent waveforms on the basis of the same, and detecting, as the same waveform section, a section composed of a plurality of continuous waveforms that have been analyzed as matching within a range according to a predetermined condition by the step. And detecting a pitch of the sound signal in the detected same waveform section. Recording medium according to symptoms. 31. A recording medium readable by a machine, having, as its storage contents, a group of instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Performing a filtering process in which a pass band is variably controlled in accordance with a frequency corresponding to each pitch in the data train, to the input sound signal; and performing the sound processing based on a sample amplitude value of the filtered sound signal. Detecting a more accurate pitch of the signal. 32. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Performing a filtering process in which a pass band is variably controlled according to a frequency corresponding to each pitch in the data sequence, to the input sound signal, and based on a continuous sample amplitude value in the filtered sound signal. Analyzing the degree of coincidence between each adjacent waveform; and Detecting, as the same waveform section, a section composed of a plurality of continuous waveforms that have been analyzed as being coincident with each other; and detecting the pitch of the sound signal in the detected same waveform section. Characteristic recording medium. 33. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Filter processing in which the pass band is time-varying controlled according to the frequency corresponding to each pitch in the data sequence,
Applying to the input sound signal; analyzing the degree of coincidence between adjacent waveforms based on continuous sample amplitude values in the filtered sound signal; and Detecting a first section consisting of a plurality of continuous waveforms that have been analyzed as being coincident with each other; and determining a plurality of waveforms before and after the detected waveform having a higher degree of coincidence in the first section. Determining a degree of coincidence with each waveform and detecting a second section having a higher degree of coincidence; and detecting a pitch of the sound signal in the detected second section. A recording medium characterized by the above-mentioned. 34. A recording medium readable by a machine, having, as its storage contents, a group of instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A step of inputting a sound signal to be analyzed; a step of performing a filtering process of a predetermined frequency band on the input sound signal; and a step of detecting a peak position of the sound signal after the filtering process. And, among various sections obtained by dividing the waveform of the sound signal between any two of the detected peak positions,
For a section having a time length commensurate with the restriction by the pass band of the filter, two pairs of adjacent sections are selected as many as possible, and the degree of coincidence of the waveforms of the two sections in each selected pair is determined. Recording, comprising: detecting a pair having the highest degree of coincidence as the same waveform section; and detecting a stationary section for sound signal analysis based on the detected same waveform section. Medium. 35. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. Is obtained by inputting a sound signal to be analyzed, detecting a peak position of the input sound signal, and dividing a waveform of the sound signal between any two peak positions. Arbitrary two adjacent among various sections
Determining the degree of coincidence of the waveforms of the two sections, connecting the sections having a high degree of coincidence to detect a first same-waveform section group, and determining a start section in the first same-waveform section group. Using the last section as a comparison target section, the degree of coincidence of the waveform is calculated for each of the sections adjacent before and after the first same waveform section group, and based on the calculated degree of match, the first same waveform section group is calculated. And detecting the same as a second same waveform section group, and detecting a steady section for sound signal analysis based on the detected second same waveform section group. A recording medium characterized by the following. 36. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Applying a first filter process in which a pass band is time-varying controlled in accordance with a frequency corresponding to each pitch in the data sequence to the input sound signal; and a sound signal subjected to the first filter process. Detecting a plurality of candidate positions serving as a period reference with respect to the frequency corresponding to each pitch in the pitch data sequence and Applying a second filter processing in which a pass band is time-varying controlled in accordance with a frequency of a predetermined integer multiple of the input sound signal; and the second filter processing corresponding to each of the detected candidate positions. Judging the degree of coincidence of the waveforms of a plurality of sections obtained by dividing the sound signal that has been subjected to the filter processing, and detecting a section having a high degree of coincidence as the same waveform section; based on the detected same waveform section Analyzing the pitch of the sound signal. 37. A recording medium readable by a machine, having, as its storage contents, a group of instructions for a program for analyzing a sound signal to be executed by a computer, and for analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Converting the difference between successive pitches in the data sequence into relative values based on the pitch cent value; and calculating a dynamic reference value based on a dynamic average of the converted relative values. And, comparing the converted relative value and the dynamic reference value,
Detecting a stationary section for sound signal analysis. 38. A recording medium readable by a machine, comprising, as its storage content, a group of instructions for a program for analyzing a sound signal to be executed by a computer, and for analyzing the sound signal. Providing a continuous sample amplitude value of an arbitrary sound signal; applying a first filter process of a predetermined characteristic to the provided continuous sample amplitude value; Creating control frequency data for a second filtering process based on the continuous sampled amplitude values subjected to the filtering process; and performing a second filtering process with characteristics based on the created control frequency data, Applying to the provided successive sample amplitude values; and providing the second filtered processed successive sample values. Recording medium characterized in that it includes a step of detecting the pitch of the sound signal based on pull amplitude value. 39. A recording medium readable by a machine, comprising, as storage contents, instructions for a program for analyzing a sound signal executed by a computer, and analyzing the sound signal. A program for inputting a sound signal to be analyzed; a step of detecting a pitch of the sound signal for each predetermined section with respect to the input sound signal, and generating a data sequence of the detected pitch; Converting the difference between successive pitches in the data sequence into relative values based on the pitch cent value; and calculating a dynamic reference value based on a dynamic average of the converted relative values. And, comparing the converted relative value and the dynamic reference value,
Detecting a stable stationary section for pitch analysis; calculating a static reference value based on a static average of the relative values within the stationary section; and the static reference value and the stationary section Comparing the relative value within the interval, detecting a pitch determination section for calculating the representative frequency of the stationary section, and based on the pitch data string in the detected pitch determination section Calculating a representative frequency of a stationary section.