JPH01219888A - Method and device for automatic sampling - Google Patents

Abstract

PURPOSE:To accurately identify a musical interval by composing musical interval identification processing of processing for extracting the peak point of power information in each section and processing for determining a musical interval in the section as a musical interval on the absolute interval base where the pitch information on the extracted peak point is closest. CONSTITUTION:A 1st dotted-line PIT indicates pitch information on an acoustic signal and a 2nd dotted curve POW indicates power information, and a longitudinal solid line VR indicates breaks of segments. Pitch information for the rise peak point of the power information has small deviation in musical interval on the absolute interval base and a musical interval is identified excellently. For the purpose, the pitch information on the rise peak point of the power information in each segment is extracted and the musical interval of the segment is identified as the musical interval on the absolute interval base where the pitch information is closest, so the musical interval is determined with high accuracy. Thus, the musical interval of each segment is identified according to the pitch information on a sampling point where the power information of the segment is given the peak value, so the musical interval can be determined excellently and the accuracy of score data is improved more.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention relates to an automatic musical notation method and apparatus for creating musical score data from acoustic signals such as singing voices, humming voices, musical instrument sounds, etc. The present invention relates to an interval identification process for identifying an interval on the absolute interval axis as an interval of .

[Prior Art] In an automatic score transcription system that converts acoustic signals such as singing voices, humming voices, and musical instrument sounds into musical score data, the basic information of musical scores such as length, pitch, key, meter, and so on are extracted from the acoustic signals. It has to detect the tempo.

By the way, the acoustic signal is only a signal that continuously includes a repeating waveform of the basic waveform, and the above-mentioned information cannot be obtained immediately.

Therefore, in the conventional automatic score transcription method, first, repetition frequency information (hereinafter referred to as pitch information) and power information of the basic waveform representing the pitch of the acoustic signal are extracted for each analysis period, and then the extracted pitch The process of dividing the acoustic signal into sections (segments) that can be considered to have the same pitch from the information and/or power information is called segmentation), and then calculates the pitch of the acoustic signal of each segment along the absolute pitch axis from the pitch information of the segments. identify the pitch,
Each piece of information was obtained in the following order: the key of the acoustic signal was determined based on the distribution information around the pitch axis of the pitch information, and the time signature and tempo of the acoustic signal were further determined based on the segment.

[Problems to be Solved by the Invention] By the way, even if an attempt is made to identify a certain segment of an acoustic signal as a pitch on the absolute pitch axis, the pitch of an acoustic signal, especially an acoustic signal uttered by a person, is not stable and cannot be the same. Even when the pitch is intended, the pitch often fluctuates. This made pitch identification processing extremely difficult.

Since pitch is a basic element of musical score data along with note length, it is necessary to identify it accurately, and if it cannot be accurately identified, the accuracy of the musical score data is reduced.

The present invention has been made in consideration of the above points, and proposes a new pitch identification method that can accurately identify pitches, and an automatic transcription method that can further improve the accuracy of final musical score data. The present invention seeks to provide methods and apparatus.

[Means for solving the problem] In order to solve the problem, in the first invention,
It is the repetition period of the input acoustic signal waveform, and includes processing to extract pitch information representing the pitch and power information of the acoustic signal, and dividing the acoustic signal into sections that can be considered to have the same pitch based on the pitch information and/or power information. In an automatic notation method that converts an acoustic signal into musical score data, the pitch identification process includes at least segmentation processing and interval identification processing that determines the pitch on the absolute pitch axis of the acoustic signal for the segmented section. The process consists of a process of extracting the peak point of the power information for each section, and a process of determining the pitch of that section to the pitch on the absolute pitch axis to which the pitch information of the extracted peak point is closest.

Further, in the second aspect of the present invention, when extracting the pitch information and the power information of the acoustic signal, which is the repetition period of the input acoustic signal waveform and representing the pitch, the pitch information and the power information are extracted. Alternatively, an acoustic system comprising, in part, a segmentation means for dividing an acoustic signal into sections that can be considered to have the same pitch based on power information, and a pitch identification means for determining the pitch on the absolute pitch axis of the acoustic signal for the divided sections. In an automatic notation device that converts a signal into musical score data, the pitch identification means includes a peak point extraction section that extracts the peak point of power information for each section divided by the segmentation means, and a peak point extraction section that extracts the peak point of power information for each section divided by the segmentation means, and a peak point extraction section that extracts the peak point of power information for each section divided by the segmentation means. It consists of a pitch determining section that determines the pitch of a section close to the pitch on the absolute pitch axis.

[Operation] In the first aspect of the present invention, since the pitch of each section is identified as a pitch on the absolute pitch axis, even if the acoustic signal fluctuates, the pitch intended by the source of the acoustic signal has the maximum volume (power information). Focusing on the fact that it is accurate when , we extracted the peak point of the power information in each section and identified the pitch information at that peak point to the closest pitch on the absolute pitch axis.

Further, the second invention similarly provides a peak point extraction unit that extracts the peak point of the power information in each segmented section based on the fact that the pitch information at the peak point of the power information is close to the intended pitch of the acoustic signal. and the pitch determining section identifies the pitch of that section to the pitch on the absolute pitch axis to which the pitch information of the extracted peak point is closest.

[Example] Hereinafter, an example of the present invention will be described in detail with reference to the drawings.

Ushigoku notation system First, the automatic notation system to which the present invention is applied will be explained.

In FIG. 3, a central processing unit (CPU) 1 controls the entire device, and performs the music transcription process shown in FIG. 4 stored in a main storage device 3 connected via a bus 2. It executes the program. Connected to the bus 2 are a keyboard 4 as an input device, a display device 5 as an output device, an auxiliary storage device 6 used as a working memory, and an analog/digital converter 7, in addition to the CPUI and main storage device 3. There is.

Connected to the analog/digital converter 7 is an acoustic signal input device 8 consisting of, for example, a microphone. This acoustic signal input device 8 captures acoustic signals such as singing or humming vocalized by a user, or musical sounds generated from musical instruments, and converts them into electrical signals, and converts the electrical signals into electrical signals. 7.

When the processing is instructed by the keyboard input device 4, the CPU starts the music transcription processing, executes the program stored in the main storage device 3, and converts the sound converted into a digital signal by the analog/digital converter 7. The signals are temporarily stored in the auxiliary storage device 6, and then the above-mentioned program is executed to convert these acoustic signals into musical score data, which is output to the display device 5 as necessary.

Next, the score transcription process performed by the CPU after capturing the audio signal will be described in detail according to the flowchart shown at the functional level in FIG. 4.

First, the CPU performs autocorrelation analysis on the acoustic signal to extract pitch information of the acoustic signal for each analysis period, performs sum-of-squares processing to extract power information for each analysis period, and then performs noise removal and smoothing processing. Execute post-processing such as (step SPI
, SP2>. After that, the CPU calculates the amount of deviation of the pitch axis of the acoustic signal from the absolute pitch axis based on the distribution status of the pitch information, and performs tuning processing to shift the obtained pitch information according to the amount of deviation. Execute (Step 5P3). That is, the pitch information is corrected so that the difference between the pitch axis of the singer or musical instrument that generated the acoustic signal and the absolute pitch axis is reduced.

Next, the CPU obtains continuous periods of pitch information in which the obtained pitch information is considered to indicate the same pitch, performs segmentation to cut the acoustic signal into segments for each note, and also calculates the obtained power. Segmentation is performed based on changes in information (step SP4.525). Based on the obtained segment information, the CPU calculates a reference length that is half the time length of a quarter note or an eighth note, and executes segmentation again based on this reference length (step 5P6). )
.

Based on the pitch information of the segments segmented in this way, the CPUI identifies the pitch of the segment to the pitch on the absolute pitch axis that can be determined to be closest to the pitch information, and further identifies the pitch of the identified continuous segment. Segmentation is performed again based on whether they are the same (step SP7.5P8).

After that, the CPU calculates the product sum of the appearance frequency of the pitch obtained by summing up the pitch information after tuning and the predetermined weighting coefficient determined according to the key, and based on the maximum information of this product sum, For example, the key of the music of the input acoustic signal is determined, such as C major or A minor, and the pitch information is reviewed for a predetermined interval on the scale in the determined key to confirm and correct the interval (step SP9 .5PI
O). Next, the CPUI performs a segmentation review based on whether or not there are any consecutive segments from the finally determined pitch, and whether or not there is a change in power between consecutive segments; Perform final segmentation (Step 5 PII
).

Once the pitch and segment are determined in this way, C
P[Jl extracts measures from the viewpoints that the song starts from the first beat, the last note of the phrase does not span the next measure, there is a break in each measure, etc., and extracts this measure information and segment tenition information. The time signature is determined from the above, and the tempo is determined from the determined time signature information and the length of the bar (steps 5P12 and 5P13).

The CPU then organizes the information on the determined pitch, length, key, time signature, and tempo, and finally creates musical score data (step 5P14).

Next, we will discuss the pitch identification process (
(see step SP7) will now be described in detail using the flowchart of FIG.

The CPU first extracts the first segment among the segments obtained by the segmentation, and then extracts the sampling point that gives the first maximum value (rising peak) of the power information from the change in the power information of that segment. Step 5P20 .21).

After that, the CPUI identifies the pitch on the absolute pitch axis that is closest to the pitch information of the sampling point giving the rising peak as the pitch of the segment (step 5P22).
>. Note that the pitch of each segment of the acoustic signal is identified as a pitch that differs by a semitone on the absolute pitch axis. C
The PUI determines whether or not the segment whose pitch has been identified through such processing is the last segment (step 5P23). As a result, if the processing has been completed, the processing program is ended, and if the processing is not completed, the process returns to step 21 described above with the next segment as the processing target (step 5P24).

By repeating the processing loop consisting of steps 5P21 to 5P24, pitch identification is performed for all segments based on pitch information at the rising peak point of the power information in the segment.

Here, the reason for using the rising peak of power information for pitch identification processing is that even though the acoustic signal has fluctuations, singers increase the volume when changing the pitch to a new sound. This is because the volume is thought to be adjusted so that the pitch is at the peak, and in fact,
It has been confirmed that there is a very high correlation between the rising peak point of power information and the pitch.

FIG. 2 shows an example of pitch identification through such processing, where the first dotted curve PIT indicates the pitch information of the acoustic signal, the second dotted curve POW indicates the power information, and the vertical solid line VR indicates the end of the segment. The pitch information at the rising peak point of each segment in this example is shown by a horizontal solid line HR, and the identified pitch is shown by a horizontal dotted line HP. As is clear from Fig. 2, the pitch information for the rising peak point of the power information has little deviation from the pitch on the absolute pitch axis;
It can be seen that pitches can be identified well.

Therefore, according to the above embodiment, the pitch information of the rising peak point of the power information of each segment is extracted, and the pitch of that segment is identified to the pitch on the absolute pitch axis to which this pitch information is closest. It can be determined with high precision. Note that since the acoustic signal is subjected to tuning processing prior to pitch identification, the pitch information for the rising peak point of the power information takes a value close to the pitch on the absolute pitch axis, making identification very easy.

In addition, since the rising peak point of power information is used, pitches can be identified better even if the segments are shorter and the number of samples is smaller than when pitch identification is performed by statistical processing of pitch information within a segment. Identification is less affected by segment length.

Note that the pitch information used in the pitch identification process may be expressed in Hz, which is a frequency unit, or may be expressed in cents, which is often used in the music field. It may be something that exists.

In addition, in the above embodiment, identification processing is performed based on pitch information for the rising peak point of power information, but pitch identification is performed based on pitch information of a sampling point that gives the maximum value of power information of this segment. You may also execute the following.

Furthermore, in the fifth embodiment described above, all the processes shown in FIG. It may also be executed using a software configuration. For example, as shown in FIG. 5, in which parts corresponding to those in FIG. The signal processing processor 13 performs an autocorrelation analysis on the acoustic signal converted to the digital signal to extract pitch information, and performs 2-Towa processing to output the power. The information may be extracted and provided to a software processing system using the CPUI. This kind of hardware configuration (1
The signal processing processor 13 used in 0 to 13) is capable of real-time processing of audio band signals, and
A processor that has an interface signal with the host CPU (for example, NEC μP D
7720) may be applied.

[Effects of the Invention] As described above, according to the present invention, the pitch of each segment is identified based on the pitch information of the sampling point that gives the peak value of the power information of the segment, so that the pitch can be determined well. The accuracy of musical score data can be further improved.

[Brief explanation of the drawing]

FIG. 1 is a flowchart showing an interval identification process according to an embodiment of the present invention, FIG. 2 is a route map showing an example of such an interval identification process, and FIG. FIG. 4 is a block diagram showing the configuration, FIG. 4 is a flowchart showing the automatic score processing procedure, and FIG. 5 is a block diagram showing another configuration of the automatic score transcription method. 1... CPU, 3... Main storage device, 6... Auxiliary storage device, 7... Analog/digital converter, 8...
Acoustic signal input device.

Claims (2)

[Claims] (1) Process of extracting pitch information representing the pitch and power information of the acoustic signal, which is the repetition period of the input acoustic signal waveform, and matching the acoustic signal based on the pitch information and/or the power information. An automatic score transcription method that converts the acoustic signal into musical score data, including at least a segmentation process that divides the acoustic signal into intervals that can be regarded as musical intervals, and an interval identification process that determines the interval on the absolute pitch axis of the acoustic signal for the segmented interval. In the above, the pitch identification process includes a process of extracting the peak point of power information for each of the divided sections, and assigning the pitch of that section to the pitch on the absolute pitch axis to which the pitch information of the extracted peak point is closest. An automatic music transcription method characterized by comprising a process of determining. (2) pitch/power extraction means for extracting pitch information, which is the repetition period of the input acoustic signal waveform and represents the pitch, and power information of the acoustic signal; Segmentation means for dividing the acoustic signal into sections that can be considered to have the same pitch;
In an automatic score transcription apparatus that converts the acoustic signal into musical score data, the automatic music transcription apparatus includes, as a part, an interval identification means for determining the interval on the absolute pitch axis of the acoustic signal for the divided section, and the interval identification means is configured as described above. a peak point extraction unit that extracts the peak point of power information for each of the sections divided by the segmentation means; and an interval that determines the pitch of the section to the pitch on the absolute pitch axis to which the pitch information of the extracted peak point is closest. An automatic score transcription device comprising: a determination section;