JP4357852B2 - Time series signal compression analyzer and converter - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a compression analyzing device and a converting device for a time-series signal that can perform efficient irreversible compression of the time-series signal and analyze the compression precision of compressed data. <P>SOLUTION: After values of respective samples are converted into predicted error values by linearly predicting the time-series signal consisting of a time-series sample array, high-order bits and low-order bits of the respective samples are separated; and high-order bit components are encoded with variable length and low-order bit components are encoded with fixed length to perform compression. The data amount of the low-order bit components is estimated as a quantization noise component and calculated and the data amount of other data generated in the compressing process is calculated; and the ratio to the data amount of the original time-series signal is calculated and the data ratios before and after the compression are comparatively displayed. <P>COPYRIGHT: (C)2004,JPO&amp;NCIPI

Description

[0001]
[Industrial application fields]
The present invention relates to the field of music production such as music production, storage of acoustic data materials, relay of location materials, especially the field of special effects by analysis / classification and processing of acoustic signals, analysis / diagnosis of biological signals in telemedicine, etc. The present invention relates to a suitable data compression analysis technique.
[0002]
[Prior art]
Conventionally, various methods are used for compression of an acoustic signal. As a method for compressing and encoding an acoustic signal, MP3 (MPEG-1 / Layer3), AAC (MPEG-2 / Layer3), and the like have been put into practical use. Such a compression encoding method makes it possible to handle an acoustic signal as small data, and contributes to the efficiency of data recording and transmission.
[0003]
MP3, AAC, and the like as described above are all referred to as lossy encoding methods, and can be efficiently compressed. However, in decoding, the original signal is completely reproduced with a considerable quality degradation. It is not possible. For this reason, in the music production field such as music production, material storage, and location material relay, these encoding methods cannot be applied, and although inefficient, a method for storing and transmitting without compression is employed. In particular, recently, the production of high-definition audio has increased, the material capacity has become enormous, and it has become a problem in managing work disks.
[0004]
Recently, in order to solve the above problems, various methods have been proposed for lossless compression coding of acoustic signals (see, for example, Patent Document 1).
[0005]
[Patent Document 1]
JP 2002-278600 A
[0006]
[Problems to be solved by the invention]
However, at present, it is possible to measure how much the original data has been compressed, but it is impossible to know how much of which component of the original signal has been compressed.
[0007]
Therefore, in order to solve such a problem, the present invention provides a time-series signal compression analysis apparatus and conversion capable of efficiently reversibly compressing a time-series signal and analyzing the compression accuracy of the compressed data. It is an object to provide an apparatus.
[0008]
[Means for Solving the Problems]
In order to solve the above problems, in the present invention, for a time-series signal composed of time-series sample sequences, an apparatus for compressing an information amount and analyzing the compressed information so that all the sample sequences can be reproduced A prediction error converting means for converting the value of each sample in the sample sequence into a prediction error value from a plurality of samples in the past in time, bit data representing each sample value converted to the prediction error value A data separation means for setting a position to be divided, dividing at a set bit position, and separating the upper sample string composed of the upper bit sample string and the lower sample string composed of the lower bit sample string; The upper sample sequence is encoded with a variable length code for the upper sample sequence, and the fixed sample code is encoded for the lower sample sequence. The lower sample encoding means, the ratio of data corresponding to the upper sample string in the time series signal, the ratio of data corresponding to the lower sample string, and the upper sample encoding means The present invention is characterized in that a data display means for displaying the data ratio and the ratio of the data encoded by the lower sample encoding means is provided.
[0009]
According to the present invention, the time series signal is subjected to prediction error conversion, the upper and lower bits are separated and compressed, the ratio of each data included in the compressed code data is displayed, and each data before compression is displayed. Since the ratio is analyzed and displayed, the time-series signal can be efficiently and reversibly compressed, and the compression accuracy of the compressed data can be analyzed.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
(Device configuration)
FIG. 1 is a block diagram showing an embodiment of a time-series signal encoding apparatus according to the present invention. In FIG. 1, 1 is time series signal input means, 2 is storage means, 3 is analysis means, 4 is display means, 5 is separation position setting means, 6 is acoustic signal conversion means, 7 is audio output means, and 10 is signal. The flat part processing means, 20 is a prediction error converting means, 30 is an inter-channel calculating means, 40 is a correlation frame detecting means, 50 is a data separating means, 60 is an upper sample encoding means, and 70 is a lower sample encoding means.
[0011]
In FIG. 1, a time-series signal input means 1 has a function of inputting a digitized acoustic signal such as a digital acoustic signal. The storage means 2 has a function of storing various data created by this apparatus. The analyzing means 3 has a function of analyzing each created data and creating data indicating the compression efficiency of this apparatus. The display unit 4 has a function of displaying the data analyzed by the analysis unit 3. The separation position setting unit 5 has a function of setting the separation position for the data separation unit 50. The acoustic signal conversion means 6 has a function of converting various data stored in the storage means into a state in which each sample can be converted into a fixed bit number, then D / A converted, amplified and output as an acoustic signal. Yes. The audio output means 7 has a function of outputting the data converted into the analog sound signal as sound. Specifically, the audio output means 7 is realized by a speaker.
[0012]
The signal flat part processing means 10 has a function of detecting a flat part having a constant signal value and efficiently encoding the sample sequence for each channel. The prediction error conversion means 20 has a function of converting the value of each sample into a prediction error value using a linear prediction error method. The inter-channel calculation means 30 has a function of performing a difference calculation between each channel of a sample row composed of a plurality of channels. Correlation frame detection means 40 detects a correlation frame in which all sample values corresponding to each frame are the same after setting a predetermined section as a frame for each sample sequence on which inter-channel computation has been performed. And has a function of deleting a correlation frame located backward in time.
[0013]
The data separation means 50 performs positive / negative polarity processing of each sample as necessary, and converts each sample constituting the error sample sequence recorded with the prediction error value into upper sample data that is upper bits at a predetermined position. It has a function of separating into lower sample data which are lower bits. The upper sample encoding unit 60 has a function of efficiently encoding the upper sample sequence separated by the data separation unit 50. The lower sample encoding unit 70 has a function of efficiently encoding the lower sample sequence separated by the data separation unit 50. Each component shown in FIG. 1 is actually realized by a computer and a dedicated software program executed by the computer.
[0014]
(Processing operation)
Next, the processing operation of the time-series signal encoding apparatus shown in FIG. 1 will be described. Here, a case of an acoustic signal having a plurality of channels as a time series signal will be described as an example. First, an analog acoustic signal that is a time-series signal is digitized. This may be performed by using a conventional general PCM method, sampling the analog acoustic signal at a predetermined sampling frequency, and converting the amplitude into digital data using a predetermined number of quantization bits. In the present embodiment, the following description will be given on the assumption that a positive / negative code is recorded with a sampling frequency of 44.1 KHz and a quantization bit number of 16 bits. When sampling is performed at a sampling frequency of 44.1 KHz, a sample string composed of 44100 samples per second is formed. Here, since the acoustic signal is composed of a plurality of channels, digitization is performed for each channel. A digitalized acoustic signal is schematically shown in FIG. FIG. 2A shows a two-channel stereo sound signal in which an L (left) signal is recorded in Ch1 and an R (right) signal is recorded in Ch2. In FIGS. 2A to 2D, the left end is the start time, and the right end is the end time. The height indicates the number of bits of each sample. In this embodiment, the height is 16 bits. Note that the time-series signal input means 1 of the present apparatus inputs the digitized acoustic signal.
[0015]
(Processing of signal flat part)
The signal flat part processing means 10 performs processing of the signal flat part on the sample sequence which is the digital sound signal digitized in this way. The signal flat portion refers to a portion where the same signal level continues. In particular, it often appears in a silent portion where the signal level is “0” and a saturated portion where the absolute value of the signal level is maximum. The silence part occurs when the sound is actually silent or when the sound is not recorded very low, but the saturation part occurs during the process of recording the signal and A / D conversion. Regardless of whether the same signal level is continuous in the silent part, the saturated part, or otherwise, the signal flat part continuously records the same signal level for a predetermined time (a predetermined number of samples). For this reason, this portion is easily compressed data. Specifically, three values of the start time position of the signal flat portion, the number of samples with the same signal level, and the signal level (sample value) are separated from the sample sequence of each channel as signal flat portion data and recorded. To do. The signal flat portion is deleted from the sample sequence of each channel. This is schematically shown in FIGS. 2B and 2C. FIG. 2B shows a sample string before the signal flat part processing. In FIG. 2B, a shaded portion indicates a signal flat portion. By the processing of the signal flat part processing means 10, the signal flat part is deleted from the original sample sequence, and becomes as shown in FIG. However, in order to restore to the original state at the time of decoding, the separated signal flat part is recorded as signal flat part data in a format as shown in FIG.
[0016]
As described above, the signal flat portion data is recorded for each signal flat portion with the three attributes of the start time (sample number), the number of samples, and the sample value. Here, the head time is the time from the start position of the signal, and in the example of FIG. 2 (e), it is recorded with the sample number from the head. When this sample number is divided by the sampling frequency, it is converted into time. The number of samples is information indicating how long the sample value continues. Note that the end time of the signal flat portion may be recorded instead of the number of samples. The sample value indicates the digitized signal level. In this embodiment, since quantization is performed with signed 16 bits, the maximum value is “32767” and the minimum value is “−32768”. That is, “0” indicates a silent portion, and “32767” and “−32768” indicate a saturated portion. However, the signal flat part processing means 10 does not process the signal flat part unconditionally. Since the present invention aims at data compression, it is meaningless if the signal flat portion data becomes larger than the reduction amount of the sample string. Therefore, the signal flat portion data is generated and separated from the sample sequence of each channel only when a predetermined number or more of samples serving as the signal flat portion are continuous.
[0017]
(Conversion to prediction error)
Subsequently, the prediction error conversion means 20 converts the value of each sample of the sample sequence that has been subjected to the signal flat part processing into a prediction error value. The calculation of the prediction error value in a certain sample is performed using the values of one or a plurality of samples immediately before being located in the past in time. In the present embodiment, a method of dynamically changing the number of samples immediately before use is used. Hereinafter, such adaptive linear predictive coding will be described. A processing outline of adaptive linear prediction encoding performed by the prediction error conversion means 20 is shown in the flowchart of FIG. First, a linear prediction error corresponding to each prediction calculation formula is calculated using a plurality of prediction calculation formulas prepared in advance (step S1). Specifically, the following [Formula 1] to [Formula 4] are prepared as prediction calculation formulas for calculating the prediction error of the sample number t.
[0018]
[Formula 1]
e1 (t) = x (t) -x (t-1) -e1 (t-1) / 2
[0019]
[Formula 2]
e2 (t) = x (t) -2 * x (t-1) + x (t-2) -e2 (t-1) / 2
[0020]
[Formula 3]
e3 (t) = x (t) −3 × x (t−1) + 3 × x (t−2) −x (t−3) −e3 (t−1) / 2
[0021]
[Formula 4]
e4 (t) = x (t) -4 * x (t-1) + 6 * x (t-2) -4 * x (t-3) + x (t-4) -e4 (t-1) / 2
[0022]
In the above [Equation 1] to [Equation 4], e1 (t) to e4 (t) are prediction errors in the sample at time t according to each prediction calculation formula, and x (t) to x (t-4) are times. It is an amplitude value from t to t-4.
[0023]
“2 × x (t−1) −x (t−2)” in the above [Expression 2], “3 × x (t−1) −3 × x (t−2) + x ( t-3) ”,“ 4 × x (t−1) −6 × x (t−2) + 4 × x (t−3) −x (t−4) ”in [Formula 4] Linear prediction component based on ~ 4 samples. Using this linear prediction component and the prediction errors “e1 (t−1) / 2” to “e4 (t−1) / 2” (error feedback component) calculated in the immediately preceding sample, a prediction error at time t e1 (t) to e4 (t) are calculated.
[0024]
Subsequently, the linear prediction error that minimizes the cumulative error, which is the cumulative absolute value of the prediction error value for each prediction calculation formula, is selected as the prediction error of the sample (step S2). Here, the concept of cumulative error is used. Specifically, cumulative values of past samples of prediction errors calculated by the respective prediction calculation formulas [Formula 1] to [Formula 4] are set as R1 to R4. Then, a prediction error corresponding to the smallest one of the accumulated errors R1 to R4 is selected. For example, it is assumed that R2 is the smallest among R1 to R4. In this case, the prediction error e2 (t) calculated by [Formula 2] is selected as the prediction error e (t) to be encoded. The selected prediction error e (t) is replaced with the original value x (t) of the sample and the subsequent processing is performed. Also, the order of the prediction formula used at this time is recorded as optimum order data in association with the sample number. The “order” is a numerical value indicating how many samples have been used in the past in calculating the prediction error, and the above [Expression 1] to [Expression 4] correspond to the first to fourth orders. For example, when the prediction error e2 (t) is selected as the prediction error e (t), the order is “2”.
[0025]
Subsequently, the absolute values of the prediction errors e1 (t) to e4 (t) are added to the accumulated errors R1 to R4 (step S3). Specifically, as shown in the following [Formula 5], the variables R1 to R4 that become the accumulated error values are updated. At the same time, each time the processing of each sample is performed, a process of incrementing the counter by one is performed.
[0026]
[Formula 5]
R1 ← R1 + | e1 (t) |
R2 ← R2 + | e2 (t) |
R3 ← R3 + | e3 (t) |
R4 ← R4 + | e4 (t) |
[0027]
Subsequently, it is determined whether the counter has exceeded a predetermined number of times (step S4). In this embodiment, this predetermined number is set as 100 times. That is, it is determined whether or not the counter exceeds 100.
[0028]
As a result, if the counter exceeds 100, the accumulated error is halved (step S5). Specifically, as shown in [Formula 6] below, variables R1 to R4 that are accumulated errors are divided by two. At the same time, the counter is reset to zero. That is, R1 to R4 here are not cumulative errors in a pure sense, but are moving averages of cumulative errors. In the present embodiment, the maximum 100 samples immediately before are accumulated, but the previous ones are processed in half. Thereby, the influence of the sample separated in time is made small.
[0029]
[Formula 6]
R1 ← (R1) / 2
R2 ← (R2) / 2
R3 ← (R3) / 2
R4 ← (R4) / 2
[0030]
By executing the processing of step S1 to step S5 over all samples at all times in the time-series signal, the values of all samples are replaced with the target error e (t) from the original amplitude value x (t). become. However, since the processing by the prediction error conversion means 20 only changes the value of each sample, the state schematically showing the acoustic signal remains as shown in FIG. Therefore, in order to distinguish the sample after processing by the prediction error conversion means 20 from the original sample, it can also be called an error sample.
[0031]
(Calculation between channels)
Next, an inter-channel difference calculation is performed by the inter-channel calculation means 30 on the sample sequence of each channel in which the prediction error value is recorded. This is done by simply taking the difference between the sample values at the same time. The result of the difference calculation is given as a sample string of one channel, and the value of the sample string of the other channel is left as it is. Specifically, in the case of a two-channel stereo sound signal as shown in FIG. 2C, the value of the L signal is recorded as it is in Ch1, and the difference value of RL is given to Ch2. In general, in a stereo sound signal, there is a correlation between the data at the same time, and the difference value between the two data at each time is a smaller value than the original value. This is the same even if the value is after the prediction code by linear prediction. Therefore, in the example of FIG. 2D, the value of each sample in Ch2 becomes small, and the room for later compression becomes large.
[0032]
(Correlation frame detection)
Subsequently, the correlation frame detecting means 40 sets a frame having a predetermined section length for the sample string of each channel for which the inter-channel calculation is performed, and compares the set frames. In this embodiment, the frame length is fixed over the entire interval from the start time to the end time of the sample string. Specifically, one frame is 512 samples. Correlation frame detection means 40 sets 512 samples from the beginning of the sample sequence of each channel as one frame, and obtains a correlation frame in which all samples match between frames. A specific procedure will be described with reference to the flowchart of FIG.
[0033]
First, the correlation frame detecting means 40 performs framing in units of a predetermined number of samples (step S11). In the present embodiment, as described above, the frame length is fixed length 512 samples over the entire section from the start time to the end time of the sample sequence. As shown in FIG. 5A, the correlation frame detection means 40 sets 512 samples from the beginning of the sample sequence as one frame.
[0034]
Next, a search is made for a frame in which all sample values constituting each frame match. Specifically, as shown in FIG. 5B, first, among the set frames, the last frame in time is set as a target frame for searching for a correlation frame. Next, within the predetermined search range, a sample having the same value as the value of the first sample of the target frame is searched while going back in time (step S12). For example, as shown in FIG. 6A, it is assumed that the target frame is composed of 512 samples kT to kT + 511. In this case, first, a sample that is the same as the sample value e (kT) of the first sample kT of the target frame is searched. Search is performed in order of sample kT-1 and sample kT-2. In FIG. 6, k indicates the k-th frame from the beginning, and T indicates the frame length (512 samples in the present embodiment).
[0035]
If a matching sample t is found (step S13), it is then compared whether the next sample t + 1 of the sample t matches the second sample kT + 1 of the target frame. In this way, as long as the sample values match, the subsequent samples are compared (step S14). In step S14, the process is repeated as long as the values of e (t + p) and e (kT + p) match. For example, in the example shown in FIG. 6B, since e (t) to e (t + 8) coincide with e (kT) to e (kT + 8), the process of step S14 is continued with p = 9. Will be. When all e (t + p) and e (kT + p) from p = 0 to p = 511 match (step S15), the sample sequence is set as a correlation frame for the target frame, and the first sample number of the correlation frame and the target frame Is recorded as frame correlation data in association with the first sample number, and the target frame is deleted from the original sample sequence (step S16). If it does not match all the samples of the target frame, the search is further made in time to determine whether there is a sample whose value matches the first sample of the target frame. If there is no matching correlation frame even after a predetermined number of samples, the search for the correlation frame related to the target frame is stopped, and the correlation frame search is performed using the frame immediately before the target frame as a new target frame. When the processing for one target frame is completed, the process returns to step S12, and the processing is continued using the immediately previous frame as a new target frame (step S17). In this way, correlation frame detection processing is performed using all frames except for a frame located near the start time of the time-series signal as target frames.
[0036]
Looking at the entire sample sequence of the time series signal, if a correlation frame corresponding to the target frame is detected as shown in FIG. 5C, the target frame is deleted as shown in FIG. 5D. Become. At this time, frame correlation data as shown in FIG. 5E is recorded so that it can be completely restored at the time of decoding. As shown in FIG. 5E, in the frame correlation data, the head sample number of the target frame and the head sample number of the correlation frame are recorded in association with each other.
[0037]
(Separation of upper and lower bits)
Subsequently, the data separation means 50 separates the upper bits and lower bits of each sample. Actually, as a pre-process before separation, the value of each sample taking a positive / negative value is converted into a bit string having a positive / negative polarity. Specifically, a bit string expressing a positive / negative value with 16 bits is converted so that the leading 1 bit is a positive / negative polarity code and the other 15 bits indicate an absolute value. When converted in this way, “0” can be omitted because no polarity code is required. As a result, the number of samples whose value is “0” × 1 bit can be reduced.
[0038]
Once the polarity processing is performed, the data separation means 50 next performs the separation of the upper bits and the lower bits of each sample. For example, when an acoustic signal is digitized by PCM and sampled with 16 quantization bits, each sample is represented by 16 bits. In this case, in this embodiment, the upper bit is separated into 12 bits and the lower bit is divided into 4 bits. This separation is basically performed in order to separate the thermal noise of a circuit used when digitizing an acoustic signal such as an A / D converter. Therefore, lower bits that are considered to be thermal noise are separated. The degree to which the lower bits are separated varies depending on the characteristics of the sound source and the circuit used, but it is preferably about 1/4 of the number of normal quantization bits. Therefore, here, 4 bits corresponding to 1/4 of 16 bits are separated as lower bits. The present invention is particularly characterized in that the separation of the upper bits and the lower bits is performed after conversion into a prediction error. This is because if conversion to prediction error is performed on the upper samples after separating the upper bits and lower bits, the compression processing is performed even if components that can be compressed by conversion to prediction errors are included in the lower bits. This is because the compression efficiency may decrease as a whole.
[0039]
Here, the state of data separation by the data separation means 50 is schematically shown in FIG. In FIG. 7, H indicates upper bits or upper sample data, and L indicates lower bits or lower sample data. FIG. 7A shows sample data before separation. The data separation means 50 separates the sample data into upper sample data shown in FIG. 7B and lower sample data shown in FIG. The sign bit included in the upper bits is included in the upper sample data as it is and separated. In the example of FIG. 7, as indicated by “H4”, when the sign bit is deleted by the preprocessing, the upper sample data without the sign bit is obtained. The sample data separated as described above will be processed separately thereafter.
[0040]
(Encoding of upper sample)
Next, the upper sample encoding means 60 encodes the separated upper samples. First, the signal flat part process is performed on the upper sample string of each channel. The signal flat part processing performed by the higher-order sample encoding means 60 is exactly the same as the processing performed by the signal flat part processing means 10. In other words, a portion where the same signal level continues in the upper sample string is composed of three values: the start time position of the signal flat portion, the number of samples that the same signal level continues, and the signal level (sample value). As the upper signal flat portion data, it is recorded separately from the upper sample string of each channel. The upper signal flat portion data is recorded in the same format as the signal flat portion data shown in FIG.
[0041]
Subsequently, the upper sample encoding means 60 converts the fixed length upper sample string into a variable length. First, a lookup table used for converting the bit configuration is created. In creating the lookup table, a histogram of each upper sample value is calculated over the entire time of the upper sample column. Since all the upper sample values are converted into absolute values by the data separating means 50, a histogram is calculated without distinguishing between positive and negative. As a result, when the sample absolute value type is 640 or more, the separator bit is a 2-bit fixed value “00”, and when the sample absolute value type is 639 or less, the separator bit is a 1-bit fixed value “0”. " Furthermore, a bit pattern having a smaller number of bits is assigned in order from the sample absolute value having the highest appearance frequency. At this time, there is a rule for the bit pattern to be assigned, and the most significant bit is always “1”. When the separator bit is 2 bits “00”, the bit pattern including the bit pattern “001” is prohibited. When the bit is 1 bit “0”, a bit pattern including a bit pattern of “01” is prohibited. Also, there is only one lookup table when the separator bit is 2 bits “00”, but the lookup table when the separator bit is 1 bit “0” is when the sample absolute value type is 320 or more. If the number is less than 320, a different one is created. Examples of lookup tables corresponding to the number of types of sample absolute values are shown in FIGS.
[0042]
Using the lookup table created as described above, the upper sample encoding means 60 converts the continuous upper sample data having a fixed length of 12 bits into a variable length bit pattern. Since it becomes a variable length, it becomes necessary to distinguish the delimiter of each data after conversion. For this reason, in the present embodiment, 1-bit or 2-bit separator bits as described above are inserted between the data. When the sample value type is less than 320, the bit string and the number of bits for expressing the data of each rank are as shown in FIG. In FIG. 8A, the rank 0 is represented by 1 bit “1” having the smallest number of bits. In FIG. 8A, the bit string before conversion is omitted, but the bit string that appears most frequently is converted to 1 bit “1”. In addition, since a separator is always added to each variable-length bit, 2 bits are required to express the data of rank 0. When the type of sample value shown in FIG. 8A is less than 320, since the separator bit is 1 bit “0”, the bit pattern “01” is not assigned.
[0043]
When the sample value type is 320 or more and less than 640, the bit string and the number of bits for expressing the data of each rank are as shown in FIG. FIG. 8B shows a new bit string obtained by adding 1 bit subsequent to the most significant 1 bit of each bit string in the lookup table shown in FIG. For example, in FIG. 8B, “10” in the ranking 0 and “11” in the ranking 1 are 1 bit “0” and “1” in “1” in the ranking 0 in FIG. 8A, respectively. In FIG. 8B, “100” in the second rank and “110” in the third rank in the second bit of “10” in the first rank in FIG. "0" and "1" are added respectively. Also in FIG. Since a separator is always added to each variable length bit, 3 bits are required to express the data of rank 0. In the example of FIG. 8B, since the separator bit is 1 bit “0”, the bit pattern of “01” is not assigned, but correct data at the time of decoding is devised by devising the order of data reading. Can be extracted.
[0044]
When the separator bit is 2 bits “00”, the bit string and the number of bits for expressing the data of each rank are as shown in FIG. In FIG. 9, the rank 0 is expressed by 1 bit “1” having the smallest number of bits. Also in FIG. 9, the bit string before conversion is omitted, but the bit string that appears most frequently is converted to 1 bit “1”. In addition, since a separator is always added to each variable length bit, 3 bits are required to express the data of rank 0. In the example of FIG. 9, since the separator bit is 2 bits “00”, the bit pattern “001” is not assigned.
[0045]
10A and 10B schematically show the state of data conversion by the higher-order sample encoding means 60. FIG. 10 (a) and 10 (b) correspond to the upper part of the sample sequence, and FIG. 10 (a) shows a state where fixed-length upper samples are continuously recorded. The high-order sample sequence as shown in FIG. 10A is converted as shown in FIG. 10B using the lookup tables shown in FIGS. 8A and 8B and FIG. .
[0046]
(Low-order sample encoding)
On the other hand, the lower sample data is processed by the lower sample encoding means 70. Specifically, the lower 2 bits of data separated by the data separation means 50 are continuously arranged.
[0047]
(Recording of code data)
The code data obtained as described above is as shown in FIG. That is, the upper variable length sample sequence, the lookup table, the upper signal flat portion data, the lower fixed length sample sequence, the frame correlation data, the signal flat portion data, and the inter-channel data. Since these data are stored in the storage means 2 during the encoding process, the data is recorded in a format that matches the recording medium to be recorded.
[0048]
(Analysis of code data)
The code data is analyzed by the analysis means 3. The process of the analysis means 3 is demonstrated using the flowchart of FIG. First, the data amount of the quantization noise component is calculated (step S21). This is calculated by measuring the data amount of the lower fixed length sample string in the code data. In the compression in this device, since a predetermined number of lower bits are originally separated as quantization components and encoded with a fixed length, the data amount of this lower fixed length sample string is the quantization noise of the original digital acoustic signal. It can be assumed that it is a component. Next, the data amount of the frame correlation data is calculated (step S22). This is done by measuring the amount of frame correlation data. Subsequently, the data amount of the target frame deleted from the original sample sequence is calculated (step S23). This is performed by calculating the data amount of the target frame deleted from the contents of the frame correlation data. Specifically, the calculation is performed by multiplying the target frame in the frame correlation data by the number of samples (512 samples in this embodiment) and the number of bits of each sample (16 bits in this embodiment).
[0049]
Next, the data amount of the signal flat portion data is calculated (step S24). This is performed by measuring the data amount of the signal flat portion data in the code data. Subsequently, the data amount of the signal flat portion of the original digital audio signal is calculated (step S25). This calculates the data amount of the original signal flat part from the content of the signal flat part data. Specifically, the calculation is performed by multiplying the number of samples in the signal flat portion data by the necessary number of bits (16 bits in this embodiment).
[0050]
Next, the data amount for each channel of the upper variable length sample string is calculated. (Step S26). This is performed by measuring the data amount for each channel of the upper variable length sample string in the code data. Subsequently, the data amount of the linear prediction target component of the original digital acoustic signal is calculated (step S27). This is based on the data amount of the quantization noise component calculated in step S21, the data amount of the deleted frame calculated in step S23, and the original signal flat portion calculated in step S25 from the data amount of the original digital audio signal. Calculated by reducing the amount of data. Since the data amount in each channel is the same, the linear prediction target component for each channel is calculated by further dividing by the number of channels. Finally, the ratio of each calculated data to the original sound signal is calculated (step S28).
[0051]
Information analyzed by the analysis means 3 is displayed on the display means 4. Here, the state of the display screen at this time is shown in FIG. In FIG. 13, the upper part shows the composition ratio of the original sound signal before compression, and the lower part shows the composition ratio of the code data after compression. Each configuration data shown in FIG. 13 is actually displayed in different colors. In addition to the configuration data, the ratio of the configuration data to the original digital audio signal is displayed as a percentage. The ratio of each configuration data is calculated and displayed as a ratio with respect to the original digital sound signal for each configuration data after compression. In the upper and lower stages, the corresponding data is displayed in the same color. For example, the linear prediction encoding target component L is displayed in the same color as the prediction encoding compression component L. Note that L and R in each data in FIG. 13 indicate channels. In the example of FIG. 13, since two-channel stereo sound signals are used as targets, two channels are shown. In the example of FIG. 13, the data amount as a whole is compressed to about 50%, and it can be seen that the predictive encoding target component, the signal flat part, and the deleted frame part contribute significantly to the compression rate.
[0052]
(Output of optimal order)
Further, the analysis unit 3 converts the optimum order data recorded by the prediction error conversion unit 20 into a predetermined display format and causes the display unit 4 to display it. The state of the screen of the display means 4 at this time is shown in FIG. In FIG. 14, the horizontal axis represents time, and the vertical axis represents the order. Displaying in the format as shown in FIG. 14 provides a reference as to what prediction formula can be used to perform optimum compression.
[0053]
(Frame correlation output)
The analysis unit 3 converts the frame correlation data recorded by the correlation frame detection unit 40 into a predetermined display format and causes the display unit 4 to display the frame correlation data. The state of the screen of the display means 4 at this time is shown in FIG. In FIG. 15, the time-series sample strings are indicated by rectangles in both the upper and lower stages. The horizontal axis represents time, the left end of the rectangle indicates the start time, and the right end indicates the end time. A vertical line segment in the upper sample row indicates a correlation frame, and a thick vertical line segment in the lower sample row indicates a target frame. The upper sample row and the lower sample row are the same, but they are displayed separately to show the relationship between the target frame and the correlation frame in an easy-to-understand manner. Corresponding correlation frames and target frames are shown connected by dotted lines. The example of FIG. 15 shows that 11 correlation frames are detected for 11 target frames. As can be seen from FIG. 15, the correlation frame is always past in time than the target frame. By outputting the analysis data as shown in FIG. 15 as visible information, it is possible to obtain information such as how much correlation there is in the time-series signal. Useful for studying effective compression.
[0054]
(Predictive error component audio output)
Apart from the visual analysis as described above, this apparatus also has a function of outputting a part of the code data or data generated in the process of generating the code data as an acoustic signal. When the sample sequence obtained by the prediction error conversion means 20 is converted by the acoustic signal conversion means and then output, the prediction error component can be output as speech. At the same time, the signal waveform is output by the display means 4. As a result, it is possible to obtain a specially effective acoustic signal that uses data that is originally a prediction error component as a new acoustic signal. For example, when processing is performed on a PCM acoustic signal having a waveform as shown in FIG. 16, a waveform prediction error component as shown in FIG. 17 is obtained.
[0055]
(Sound output of upper prediction error component)
Further, when the upper fixed length sample sequence generated in the generation process of the upper variable length sample sequence is converted by the acoustic signal converting means and then output, the upper bit component of the prediction error component can be output as speech. At the same time, the signal waveform is output by the display means 4. As a result, a special effective acoustic signal is obtained in which the data that is essentially the main component of the prediction error component is used as a new acoustic signal. For example, when processing is performed on a PCM acoustic signal having a waveform as shown in FIG. 16, a higher order prediction error component of the waveform as shown in FIG. 18 is obtained.
[0056]
(Lower prediction error component audio output)
Further, when the lower fixed-length sample sequence is converted by the acoustic signal converting means and then output, the lower bit component of the prediction error component can be output as speech. At the same time, the signal waveform is output by the display means 4. As a result, a special effective acoustic signal is obtained in which the data that is originally the quantization noise component of the prediction error component is used as a new acoustic signal. For example, when processing is performed on a PCM acoustic signal having a waveform as shown in FIG. 16, a lower prediction error component of the waveform as shown in FIG. 19 is obtained.
[0057]
(Decryption)
Next, decoding of code data encoded by the encoding device will be described. FIG. 20 is a functional block diagram showing the configuration of the time-series signal decoding apparatus according to the present invention. In FIG. 20, 91 is a data reading means, 92 is a high-order sample converting means, 93 is a data integrating means, 94 is a frame restoring means, 95 is a channel restoring means, 96 is an independent sample restoring means, and 97 is a signal flat part inserting means. is there. The configuration shown in FIG. 20 is realized by a computer and a dedicated software program installed in the computer.
[0058]
Next, the processing operation of the decoding device shown in FIG. 20 will be described. First, the data reading means 91 reads a recording medium on which code data as shown in FIG. 11 is recorded. The data reading unit 91 passes the upper variable length sample string and the lookup table among the read data to the upper sample conversion unit 92. By referring to the lookup table, the upper sample conversion means 92 restores an upper fixed length sample sequence having a fixed length of 12 bits (11 bits for values of “0”) from the upper variable length sample sequence. go. At this time, if the lookup table is as shown in FIG. 8A or FIG. 9, there is no problem if the bit data of the upper variable length sample sequence is read and restored in order, but FIG. In the case of the lookup table as shown in b), it is necessary to devise at the time of conversion. In this case, since the separator bit is 1 bit “0”, the bit pattern “01” should be prohibited originally, but as shown in FIG. 8B, the converted bit string contains “01”. Some of them contain bit patterns. Therefore, in the present embodiment, this is dealt with by changing the bit pattern writing order. Specifically, in the case of FIG. 8A or FIG. 9, the first bit that is always 1 is written last, the second bit is written, and in FIG. 8B, the first and second bits are written. Is written last, and is written from the third bit. For example, the bit string “101” in the fourth rank includes a bit pattern “01”. In such a bit string, first, the third bit “1” is read, and is composed of a separator bit and a first bit. Since the “01” pattern is recognized and the second bit is read last, there is no erroneous recognition of the separator. In this case, the upper sample conversion means 92 recognizes the bit string “101” and can restore the original fixed-length bit string according to the lookup table.
[0059]
Further, the upper sample conversion means 92 inserts the read upper signal flat portion data into a predetermined position of the upper fixed length sample string. Subsequently, the data integration unit 93 integrates the upper fixed length sample string and the lower fixed length sample string. Specifically, 12 bits are extracted from the upper fixed-length sample sequence, 4 bits are extracted from the lower fixed-length sample sequence, and integration processing is performed sequentially. Further, subsequently, the data integration means 93 converts the sample string expressed by the positive / negative positive / negative polarity part 1 bit and the numerical value part 15 bits into 16 bits taking a positive / negative numerical value.
[0060]
For such a sample string, the frame restoration means 94 defines, in the frame correlation data, a section having the same sample string as the sample string in the section corresponding to the correlation frame defined in the frame correlation data. The frame is restored by inserting it at the address position of the target frame. As a result, the sample sequence as shown in FIG. 2D is restored. Further, the channel restoration means 95 uses the inter-channel information to recognize which channel's sample sequence is the original and which channel's sample sequence is the difference information from which channel's sample sequence. Restore the sample column. At this time, since the value of each sample is recorded with a prediction error based on any number of sample values from the previous one to four, the independent sample restoration means 96 performs the above [Expression 1] to [Expression 4]. ], The original sample value x (t) is sequentially restored on the basis of the expression obtained by exchanging the term on the left side and the first term on the right side. Finally, the signal flat portion inserting means 97 uses the signal flat portion data as shown in FIG. 2 (e) to insert the signal flat portion at a predetermined position of the sample row as shown in FIG. 2 (b). To do. As a result, the digital audio signal in a state where the analog signal is converted to PCM is restored without data loss.
[0061]
【The invention's effect】
As described above, according to the present invention, with respect to a time-series signal composed of time-series sample sequences, the values of the samples in the sample sequence are predicted error values from a plurality of samples in the past in time. A bit data representing each sample value converted to a prediction error value is set to a position where the bit data is divided, the bit data is divided at the set bit position, and a high-order sample string composed of a high-order bit sample string, Separated into lower-order sample sequences composed of lower-order bit sample sequences, upper-order sample sequences are encoded with variable-length codes, and lower-order sample sequences are encoded with fixed-length codes. In the time series signal, the ratio of data corresponding to the upper sample string, the ratio of data corresponding to the lower sample string, the ratio of data encoded by encoding the upper sample, and the encoding of the lower sample Sign Since so as to display the rate of data, time-series signals as well as efficient lossless compression, an effect that a compression accuracy of the compressed data can be analyzed.
[Brief description of the drawings]
FIG. 1 is a functional block diagram showing an embodiment of a time-series signal encoding apparatus according to the present invention.
FIG. 2 is a diagram showing a state of processing by a signal flat part processing unit 10 and an inter-channel calculation unit 30.
FIG. 3 is a diagram showing a state of a prediction error calculation process by a prediction error conversion means 20;
FIG. 4 is a flowchart showing processing by the inter-frame calculating means 40.
FIG. 5 is a diagram showing an overall state of a time-series signal by processing of an inter-frame calculating unit 40.
FIG. 6 is a diagram showing a state of samples compared by the processing of the inter-frame calculating means 40.
7 is a diagram showing a state of processing by a data separating means 50. FIG.
FIG. 8 is a diagram illustrating an example of a lookup table when the type of sample absolute value is less than 640.
FIG. 9 is a diagram illustrating an example of a lookup table when the type of sample absolute value is 640 or more.
FIG. 10 is a diagram schematically illustrating the conversion of the bit length of an upper sample.
FIG. 11 is a diagram showing code data obtained by the time-series signal encoding apparatus according to the present invention.
FIG. 12 is a flowchart showing a state of processing by the analyzing means 3;
FIG. 13 is a diagram showing a display example of each data ratio processed by the analysis means 3;
FIG. 14 is a diagram showing optimum order data displayed on the display means 4;
FIG. 15 is a diagram showing the frame correlation displayed on the display means 4;
FIG. 16 is a diagram illustrating a waveform of an original sound signal.
17 is a diagram showing a waveform of a prediction error component obtained by processing the original sound signal of FIG.
18 is a diagram showing a waveform of a higher order prediction error component obtained by processing the original sound signal of FIG.
19 is a diagram showing a waveform of a lower prediction error component obtained by processing the original sound signal of FIG.
FIG. 20 is a functional block diagram showing a time-series signal decoding apparatus.
[Explanation of symbols]
1 ... Time-series signal input means
2. Storage means
3. Analytical means
4. Display means
5 ... Separation position means
6 ... Acoustic signal conversion means
7 ... Audio output means
10: Signal flat part processing means
20 ... Prediction error conversion means
30 ... Channel calculation means
40. Interframe calculation means
50. Data separation means
60: Upper sample encoding means
70 ... Lower sample encoding means
91 ... Data reading means
92 ... Upper sample conversion means
93. Data integration means
94 ... Frame restoration means
95: Channel restoration means
96 ... Independent sample restoration means
97 ... Signal flat part insertion means

Claims (8)

An apparatus for compressing the information amount and analyzing the compressed information so that all the sample sequences can be reproduced with respect to a time-series signal composed of time-series sample sequences,
Prediction error conversion means for converting the value of each sample in the sample sequence into prediction error values from a plurality of samples in the past in time;
Set a position to divide bit data representing each error sample value converted to the prediction error value, divide at the set bit position, and an upper sample string composed of upper bit sample strings and lower bits A data separation means for separating the data into a lower sample sequence composed of a plurality of sample sequences;
For the upper sample sequence, upper sample encoding means adapted to perform encoding with a variable length code;
For the lower sample sequence, lower sample encoding means for encoding with a fixed length code;
The ratio of data corresponding to the upper sample string, the ratio of data corresponding to the lower sample string, the ratio of data encoded by the upper sample encoding means, and the lower sample in the time series signal A data display means for displaying a ratio of data encoded by the encoding means;
A time-series signal compression analysis apparatus. In claim 1,
In the sample sequence, a signal flat portion in which the sample values are continuously the same value is extracted, separated from the sample sequence, and the start time position of the separated sample, the number of samples, and the sample value A signal flat part encoding means for encoding three values as signal flat part data;
The time-series signal compression analysis apparatus, wherein the data display means further displays the ratio of the signal flat part and the ratio of the signal flat part data. In claim 1,
When the sample string is composed of a plurality of channels having a plurality of values at the same time, an inter-channel calculation is performed by applying a predetermined calculation to the sample string between the channels and updating the sample string of any channel. Further comprising means,
The time-series signal compression analysis apparatus, wherein the data display means further displays the ratio of each data for each channel. In claim 1,
By setting a frame composed of a predetermined number of sample sequences from the sample sequence and searching for past samples in time with each frame as a target frame, all samples are all samples of the target frame. It is detected whether or not there is a correlation frame having the same value, and when there is a correlation frame, information associating the target frame with the correlation frame is encoded as frame correlation data, and each sample of the target frame is encoded with the sample sequence. Further comprising a frame detection means for deleting from
The time series signal compression analysis apparatus, wherein the data display means further displays the position of the target frame in the time series signal when the ratio of each data is displayed. A device that compresses the amount of information so that all the sample sequences can be reproduced and converts the data created in the compression process into an acoustic signal and outputs it to a time-series signal composed of time-series sample sequences. There,
Prediction error conversion means for converting the value of each sample in the sample sequence into prediction error values from a plurality of samples in the past in time;
Set a position to divide bit data representing each error sample value converted to the prediction error value, divide at the set bit position, and an upper sample string composed of upper bit sample strings and lower bits A data separation means for separating the data into a lower sample sequence composed of a plurality of sample sequences;
For the upper sample sequence, upper sample encoding means adapted to perform encoding with a variable length code;
For the lower sample sequence, lower sample encoding means for encoding with a fixed length code;
Acoustic signal conversion means for converting the data created in the prediction error conversion means or data separation means into an acoustic signal;
Voice output means for outputting the converted acoustic signal as voice;
Display means for displaying the converted acoustic signal as a waveform;
A time-series signal conversion device characterized by comprising: In claim 5,
It said acoustic signal conversion means converting apparatus of the time-series signal, wherein the converted sample sequence in the prediction error converter means is for converting an acoustic signal. In claim 5,
The time-series signal conversion apparatus according to claim 1, wherein the acoustic signal conversion means converts the upper sample sequence separated by the data separation means into an acoustic signal . In claim 5,
The time-series signal conversion apparatus according to claim 1, wherein the acoustic signal conversion means converts the lower sample sequence separated by the data separation means into an acoustic signal .

Images