JP3223564B2 - Pitch extraction method - Google Patents

Abstract

PURPOSE:To enable secure pitch extraction even when the rising or falling peak level of a speech varies acutely. CONSTITUTION:An input speech signal which is taken out by a block takeout processing part 10 is divided into plural subordinate blocks by a subordinate block division processing part 15. A peak level detection part 16 extracts a peak level from each of the subordinate blocks of the input speech signal. A maximum peak level detection part 17 detects the maximum peak level among the peak levels of the subordinate blocks. A comparison part 18 compares the maximum peak level of each of the subordinate blocks and sends the comparison result to a clipping level control part 19. The clipping level control part 19 varies the clipping level of a center clipping process part 12 stepwise or continuously in the blocks.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a pitch extracting method for extracting a pitch from an input audio signal waveform.

[0002]

2. Description of the Related Art Voices are classified into voiced sounds and unvoiced sounds. Voiced sound is observed as a periodic vibration in a voice accompanied by vocal cord vibration. Unvoiced sound is speech that is not accompanied by vocal cord vibration and is observed as aperiodic noise. Most of ordinary voices are voiced, and unvoiced sounds are only special consonants called unvoiced consonants. The period of a voiced sound is determined by the period of vocal cord vibration, which is called a pitch period, and the reciprocal thereof is called a pitch frequency. These pitch periods and pitch frequencies are important factors that determine the pitch and intonation of the voice. Therefore, the pitch period is accurately extracted from the original voice waveform (hereinafter, referred to as
Pitch extraction) is important in the speech synthesis process of analyzing and synthesizing speech.

The above-mentioned pitch extraction method (hereinafter referred to as a pitch extraction method) includes a waveform processing method for detecting a periodic peak on a waveform, a correlation processing method utilizing the fact that correlation processing is strong against phase distortion of a waveform, and a spectrum processing method. And a spectrum processing method using a periodic frequency structure.

An autocorrelation method, which is one of the above-mentioned correlation processing methods, will be described below with reference to FIG. A in FIG.
FIG. 11B shows a waveform obtained by calculating the autocorrelation function of x (n) indicated by A in FIG. Also, C in FIG. 11 is a waveform C [x (n)] center-clipped at the clipping level C _L shown in A.
D in FIG. 4 is a waveform R _c (k) obtained by obtaining the autocorrelation of C [x (n)] indicated by C.

As described above, when the autocorrelation function of the input speech waveform x (n) for 300 samples shown in FIG. 11A is obtained, a waveform R _x (k) shown in FIG. 11B is obtained. This FIG.
In the waveform R _x (k) of the autocorrelation function shown in B of FIG. 7, a strong peak is observed at the pitch period. However, there are many extra peaks due to the vocal tract damping vibration. To reduce this extra peak autocorrelation from the center clip waveform C [x (n)] shown in C of FIG. 11 crushed small waveform as an absolute value than the clipping level ± C _L shown in A of FIG. 11 It is possible to issue a function. In this case, FIG.
In the center-clipped waveform C [x (n)] shown in C of FIG. 1, only a few pulses remain at the original pitch interval, and the autocorrelation function R
_{The c} (k) waveform has fewer extra peaks.

The pitch obtained by the above pitch extraction is
As described above, it is an important factor in determining the pitch and intonation of a voice, and accurate pitch extraction from an original voice waveform is applied to, for example, high-efficiency coding of a voice waveform.

[0007]

Conventionally, when a pitch is obtained from the peak of the autocorrelation of an input speech waveform, the clipping level is set so that the peak to be obtained by the center clip comes out sharply. Specifically, the clipping level is set low so that a signal of a minute level is not lost due to clipping.

Therefore, if the input level fluctuates rapidly in the same frame, such as when the sound starts, when the clipping level is low, an extra peak is generated when the input level increases. Therefore, almost no clipping effect is obtained, and pitch extraction may become unstable.

[0009] Therefore, the pitch extraction method according to the present invention comprises:
The present invention has been made in view of the above circumstances, and proposes a pitch extraction method that enables reliable pitch extraction even when the level of the input speech waveform changes rapidly in the same frame.
For the purpose of offering.

[0010]

According to the pitch extracting method of the present invention, an input audio signal waveform is extracted in units of blocks.
In a pitch extracting method for center-clipping an audio signal waveform in the block and extracting a pitch based on the center-clipped signal, the block is divided into a plurality of sub-blocks, and a clip level is set for each sub-block. The above problem is solved by changing the clipping level in the block based on the clip level at the time of center clipping.

Further, in the pitch extracting method according to the present invention, a peak level in a plurality of sub-blocks is obtained as a clipping level, and when the fluctuation of the peak level is larger than a predetermined value, the clipping level at the time of the center clip is clipped. The above problem is solved by changing within the block based on the usage level.

Here, the clipping level at the time of the center clip may be changed stepwise within the block.
Alternatively, it may be changed continuously.

[0013]

According to the pitch extracting method of the present invention, an input audio signal waveform extracted in units of blocks is divided into a plurality of sub-blocks, and a clipping level in the block is determined based on a clip level obtained for each of the sub-blocks. The pitch can be reliably extracted by changing.

Further, the pitch extracting method according to the present invention is characterized in that when the peak level between adjacent sub-blocks among the plurality of sub-blocks greatly fluctuates, the clipping level is changed within the block to ensure the pitch extraction. Can be.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the pitch extracting method according to the present invention will be described below with reference to the drawings. FIG. 1 is a functional block diagram for explaining the functions of the embodiment of the pitch extracting method according to the present invention. In FIG. 1, in the present embodiment, a block extraction processing unit 10 for extracting an input audio signal supplied from an input terminal 1 in block units, and clipping from one block of the input audio signal extracted by the block extraction processing unit 10 A clipping level setting unit 11 for setting a level;
A center clip processing unit 12 for center clipping a block, and an autocorrelation calculation unit 1 for calculating an autocorrelation from a center clip waveform from the center clip processing unit 12
3 and a pitch calculator 14 for calculating a pitch from the autocorrelation waveform from the autocorrelation calculator 13.

Here, the clipping level setting unit 1
Reference numeral 1 denotes a sub-block that divides one block of the input audio signal supplied from the block extraction processing unit 10 into a plurality of sub-blocks (in this embodiment, is divided into two sub-blocks, a first half and a second half) A division processing unit 15;
A peak level extraction unit 16 that extracts a peak level in each sub-block from the first half and the second half of the input audio signal divided by the sub-block division processing unit 15;
A maximum peak level detector 17 for detecting the maximum peak level in the first half and the second half (hereinafter referred to as a maximum peak level) from the peak level extracted by the peak level extractor 16, and a maximum peak level detector 17 A comparing unit 18 for comparing the maximum peak level in the first half part and the maximum peak level in the second half part based on a certain condition;
There is a clipping level control unit 19 that sets a clipping level from the comparison result from the comparison unit 18 and the two maximum peaks from the maximum peak detection unit 17 and controls the center clip processing unit 12.

The peak level extracting section 16 includes sub-block peak level extracting sections 16a and 16b. The sub-block peak level extraction unit 16a extracts a peak level from the first half divided by the sub-block division processing unit 15. The sub-block peak level extracting unit 16b extracts a peak level from the latter half divided by the sub-block dividing unit 15.

The maximum peak detector 17 comprises sub-block maximum peak level detectors 17a and 17b. The sub-block maximum peak level detector 17a
Detects the maximum peak level of the first half from the peak level of the first half extracted by the sub-block peak level extraction unit 16a. The sub-block maximum peak level detection unit 17b detects the second half maximum peak level from the second half peak level extracted by the sub block peak level extraction unit 16b.

Next, the operation of the present embodiment comprising the functional block shown in FIG. 1 will be described with reference to the flowchart shown in FIG. 2 and the waveform chart shown in FIG.

First, when the flowchart of FIG. 2 is started, in step S1, an input audio signal waveform is extracted in block units. Specifically, the input audio signal is multiplied by a window function,
The input audio signal waveform is cut out by partially overlapping (overlapping), and one frame (25) shown in FIG.
(6 samples) of the input audio signal waveform is obtained, and the process proceeds to step S2.

In step S2, one block of the input audio signal extracted in step S1 is further divided into a plurality of sub-blocks. For example, in the input audio signal waveform of one block shown in FIG. 3A, n = 0, 1,.
27 is the first half, and n = 128, 129,..., 255 is the second half. Then, the process proceeds to step S3.

In step S3, the peak levels of the input audio signal waveforms in the first half and the second half divided in step S2 are extracted. This is the operation of the peak level extraction unit 16 in FIG.

[0023] In step S4, detects a maximum peak level P ₁ and P ₂ in each of the sub-blocks from the peak level of the front half portion and the latter half portion extracted in step S3. This is the operation of the maximum peak level detector 17 in FIG.

In step S5, the maximum peak levels P1 in the first half and the second half detected in step S4.
And P2 are compared under a certain condition to determine whether or not the level of the input audio signal waveform fluctuates greatly within one frame. The certain condition here means that the maximum peak level P1 in the _first half is changed to the maximum peak level P2 in the _second half by the coefficient k (0 <0).
k <1) is smaller than the value obtained by multiplying the or the coefficient k (0 to a maximum peak level P ₁ of the front half portion <k <1) it is less the maximum peak level P ₂ of the second half portion than the value obtained by multiplying a thing called It is. Therefore, in this step S5, P ₁
<K · P ₂ or, k · P _1> compares the maximum peak level P ₁ and P2 of the first half and the second half portion under the condition that P _2. This is the operation of the comparison unit 18 in FIG. When the maximum peak levels P ₁ and P ₂ of the first half and the second half are compared based on the above conditions in step S5, it is determined that the level of the input audio signal greatly fluctuates within one frame (YES). Proceeding to S6, if it is determined that the level change of the input audio signal is not intense within one frame (NO), the process proceeds to step S7.

In step S6, in response to the result of the determination in step S5 that the maximum level fluctuates greatly, the clipping level is calculated differently. For example, in FIG. 3B, the clip level in the first half (0 ≦ n ≦ 127) is set to k · P ₁ , and the clip level in the second half (128 ≦ n ≦ 255) is set to k · P ₂ . .

On the other hand, in step S7, the result of determination in step S5 that the level of the input audio signal does not vary greatly within one block is received, and the clipping level is unified and calculated. For example, a maximum peak level P _1,
Clipping smaller one to a level obtained by multiplying the k of the maximum peak level P ₂ (e.g., k · P ₁ or k · P ₂₎ is set.

Steps S6 and S7 are the operations of the clipping level control section 19 in FIG.

Then, in step S8, the center clip processing of one block of the input audio waveform is performed at the clipping level set in step S6 or step S7. This is the operation of the center clip processing unit 12 in FIG. Then, the process proceeds to step S9.

In step S9, an autocorrelation function is calculated from the center clip waveform obtained by the center clip processing performed in step S8. This is the operation of the autocorrelation calculator 13 in FIG. Then, the process proceeds to step S10.

In step S10, a pitch is extracted from the autocorrelation function obtained in step S9. This is the operation of the pitch calculator 14 in FIG.

In FIG. 3A, N = 0, 1,..., 2
55 is a diagram showing an input audio waveform in which 256 samples of 55 are set as one block, where N = 0, 1,... 127 is a first half, N = 128, 129. The maximum peak level of the absolute value of the waveform is obtained within 100 samples up to N = 0, 1,... 99 in the first half and 100 samples up to N = 156, 157.255 in the second half, and P ₁ , It is set to P _2. Here, for example, when P ₁ = 1 and P ₂ = 3 as shown in FIG.
Assuming that the value of k is 0.6, P ₁ (= 1) <k · P
₂ (= 1.8). At this time, assuming that the level fluctuation of the input audio signal waveform is large, the clip level of the first half is set to k · P ₁ = 0.6, and the clip level of the second half is set to k · P ₂ = 1.8. FIG. 3B shows this clipping level. The waveform subjected to the center clipping process at the clipping level shown in FIG. 3B is the waveform shown in FIG. 3C. If the autocorrelation function of the waveform subjected to the center clipper processing shown in FIG. 3C is taken, it becomes as shown in FIG. 3D. Then, the pitch can be calculated from D in FIG.

Here, the clipping level in the center clip processing unit 12 is not only changed stepwise in the block as described above, but also continuously changed as shown by a broken line in FIG. 3B. Is also good.

Next, an MBE (Multiband Excitation) vocoder, a kind of speech signal synthesis / analysis coding apparatus (so-called vocoder) to which the pitch extraction method according to the present invention can be applied, will be described with reference to the drawings. . This MBE vocoder is compatible with DW Griffin and J.
S. Lim, "Multiband Excitation Vocoder," IEEE Trans.
Acoustics, Speech, and Signal Processing, vol.36, N
o.8, pp.1223-1235, Aug.1988, and a conventional PARCOR (PARtial auto-CORrelatio).
n: partial autocorrelation) In a vocoder or the like, a voiced section and an unvoiced section are switched for each block or frame at the time of speech modeling, whereas in the MBE vocoder,
The model is modeled on the assumption that a voiced (Voiced) section and an unvoiced (Unvoiced) section exist in the frequency domain at the same time (in the same block or frame).

FIG. 4 is a block diagram showing an overall schematic configuration of an embodiment in which the present invention is applied to the MBE vocoder. In FIG. 4, an audio signal is supplied to an input terminal 101, and this input audio signal
The signal is sent to a filter 102 such as a PF (high-pass filter) to remove a so-called DC (direct current) offset and to remove at least a low-frequency component (200 Hz or less) for band limitation (for example, limited to 200 to 3400 Hz). . The signal obtained through the filter 102 is sent to the pitch extraction unit 103 and the windowing processing unit 104, respectively. In the pitch extracting section 103, the input audio signal data is divided into blocks (or cut out by a rectangular window) in units of a predetermined number N (for example, N = 256), and the pitch of the audio signal in this block is extracted. . For example, as shown in FIG. 5A, L (for example, L = 16)
0), and the overlap between the blocks is NL samples (for example, 9 frames).
6 samples). The windowing processing unit 104
In this example, a predetermined window function, for example, a Hamming window is applied to one block N samples, and the windowed block is sequentially moved in the time axis direction at intervals of one frame L samples.

When such a windowing process is represented by a mathematical formula, _xw (k, q) = x (q) w (kL-q) (1) In the equation (1), k is a block number,
q represents a time index (sample number) of the data. The q-th data x (q) of the input signal before processing is windowed by a window function w (kL-q) of the k-th block. This shows that data x _w (k, q) can be obtained. 5A in the pitch extracting unit 103
The window function w _r (r) in the case of a square window as shown in the following equation is obtained by: w _r (r) = 1 0 ≦ r <N (2) = 0 r <0, N ≦ r The window function w _h (r) in the case of the Hamming window as shown in FIG. 5B in the unit 104 is given by w _h (r) = 0.54−0.46 cos (2πr / (N−1)) 0 ≦ r <N (3) = 0 r <0, N ≦ r When such a window function w _r (r) or w _h (r) is used, the window function w (r) (= w (kL−
The non-zero section of q)) is expressed as follows: 0 ≦ kL−q <N By modifying this, kL−N <q ≦ kL Therefore, for example, in the case of the rectangular window, the window function w _r (kL−q) =
As shown in FIG. 6, kL-N <q ≦ kL
It is time of. Further, the above equations (1) to (3) indicate that the length N
(= 256) indicates that the sample window advances by L (= 160) samples. Hereinafter, the above (2)
Each N point (0 ≦ r) extracted by each window function of the equation (3)
<N) are represented by x _wr (k, r) and x _wh , respectively.
(k, r).

As shown in FIG. 7, the windowing processing unit 104 _applies 179 to the sample sequence x _wh (k, r) of 256 samples per block to which the Hamming window of the above equation (3) has been applied.
Two samples of 0 data are added (so-called zero-filled) to make 2048 samples, and the orthogonal transform unit 105 performs orthogonal transform such as FFT (fast Fourier transform) on the time axis data sequence of 2048 samples. Processing is performed.

In the pitch extracting section 103, the above x _wr (k, r)
Is extracted based on the sample sequence (1 block N samples). As the pitch extraction method, as described above, a method using a periodicity of a time waveform, a periodic frequency structure of a spectrum, an autocorrelation function, and the like are known.
This apparatus employs the autocorrelation method of the center clip waveform as described above. As for the center clip level in the block at this time, one clip level may be set for one block. However, in the present apparatus, as described above, each part (each sub block) obtained by subdividing the block is used.
Is detected, and when the difference between the peak levels of these sub-blocks is large, the clip level is changed stepwise or continuously within the block.

The pitch period is determined based on the peak position of the autocorrelation data of the center clip waveform. At this time, a plurality of peaks are obtained from the autocorrelation data belonging to the current frame (the autocorrelation is obtained from data of one block N samples), and the maximum peak among the plurality of peaks is equal to or larger than a predetermined threshold. In the case of, the maximum peak position is used as the pitch period, otherwise,
Within a pitch range that satisfies a predetermined relationship with respect to the pitch obtained in a frame other than the current frame, for example, the previous and next frames, for example, ± 20% around the pitch of the previous frame
Is determined, and the pitch of the current frame is determined based on the peak position. The pitch extraction unit 103 performs a relatively rough pitch search using an open loop, and the extracted pitch data is sent to a high-precision (fine) pitch search unit 106, and a high-precision pitch search (pitch) using a closed loop is performed. Fine search) is performed.

High precision (fine) pitch search section 106
Contains the coarse (rough) pitch data of the integer value extracted by the pitch extracting unit 103 and the orthogonal transform unit 10.
5, for example, the data on the frequency axis that has been subjected to the FFT. In the high precision pitch search unit 106,
With the coarse pitch data value as the center, ± 0.2 steps
Shake several samples at a time to drive to the optimal fine pitch data with a decimal point (floating). At this time, as a method of fine search, a so-called analysis by synthesis method is used, and the pitch is selected so that the synthesized power spectrum is closest to the power spectrum of the original sound.

The fine search of the pitch will be described. First, in the MBE vocoder, the FF
S (j) as spectral data on the frequency axis orthogonally transformed by T or the like is expressed as S (j) = H (j) | E (j) | 0 <j <J (4) Model is assumed. Where J is
ω _s / 4π = fs / 2 in response, the sampling frequency f
_s = when ω _s / 2π is, for example, 8kHz corresponding to 4kHz. In the above equation (4), when the spectrum data S (j) on the frequency axis has a waveform as shown in FIG.
(j) represents the original spectrum data S as shown in FIG.
(j) shows the spectral envelope,
(j) shows the spectrum of the excitation signal (excitation) at the same level and periodic as shown in FIG. 8C. That is, the FFT spectrum S (j) has a spectrum envelope H (j) and a power spectrum | E of the excitation signal.
(j) Modeled as the product with |.

Power spectrum | E (j) of the above excitation signal
| Takes into account the periodicity (pitch structure) of the waveform on the frequency axis determined according to the pitch, and converts the spectrum waveform corresponding to the waveform of one band (band) for each band on the frequency axis. It is formed by arranging it repeatedly. The waveform for one band is obtained by performing a FFT by regarding a waveform obtained by adding 0 data for 1792 samples (padding) to a Hamming window function of 256 samples as shown in FIG. 7 as a time axis signal, for example. It can be formed by cutting out an impulse waveform having a certain bandwidth on the frequency axis according to the pitch.

Next, for each band divided according to the pitch, a value (a kind of amplitude) | A representative of the above H (j) (to minimize the error for each band) | A _m
| Here, for example, when the lower and upper points of the m-th band (band of the m-th harmonic) are a _m and b _m , respectively, the error ε _m of the m-th band is

[0043]

(Equation 1)

Can be expressed by | A _m | that minimizes this error ε _m is

[0045]

(Equation 2)

When | A _m | in the equation (6),
Minimize the error ε _m . The amplitude | A _m | is obtained for each band, and the error ε _m for each band defined by the above equation (5) is obtained using the obtained amplitude | A _m |. Next, a total value Σε _m of all the bands of the error ε _m for each band is obtained. Further, the error sum Shigumaipushiron _m of all such bands, calculated for different pitches to some small, obtaining the pitch as an error sum Shigumaipushiron _m is minimized.

That is, several types are prepared vertically, for example, in increments of 0.25 with the rough pitch obtained by the pitch extraction unit 103 as the center. Each respective pitches of different pitches to these plurality of types of fine finding the error sum Σε _m. In this case, when the pitch is determined, the bandwidth is determined. From the above equation (6), the power spectrum | S (j) | of the data on the frequency axis and the excitation signal spectrum | E
(j) | seek error epsilon _m of equation (5) using a, can be obtained sum Shigumaipushiron _m of all the bands. Obtains the error sum Shigumaipushiron _m for each pitch, is not to determine the pitch corresponding to error sum total value which is the smallest as the optimal pitch. As described above, the optimum fine (for example, in increments of 0.25) pitch is obtained by the high-precision pitch search unit 106, and the amplitude | A _m |
Is determined.

In the above description of the fine search of the pitch, in order to simplify the description, all the bands are voiced (Vo).
iced), but the MBE
In a vocoder, an unvoiced sound (Un
Since the model in which a voiced) region exists is used, it is necessary to discriminate voiced / unvoiced sounds for each band.

The data of the optimum pitch and amplitude | A _m | from the high-precision pitch search unit 106 is sent to the voiced / unvoiced sound discriminating unit 107, and the voiced / unvoiced sound is discriminated for each band. For this determination, NSR (noise-to-signal ratio) is used. That is, the NSR of the m-th band is

[0050]

(Equation 3)

When the NSR value is larger than a predetermined threshold value (for example, 0.3) (error is large), | S (j) by | A _m || E (j) | | Is not good (the excitation signal | E (j) | is inappropriate as a basis), and the band is identified by UV (Unvoice
d, unvoiced sound). In other cases, it can be determined that the approximation has been performed to some extent, and the band is
(Voiced, voiced sound).

Next, the amplitude re-evaluation unit 108 receives the on-frequency data from the orthogonal transformation unit 105 and the amplitude | A _m evaluated as a fine pitch from the high-precision pitch search unit 106.
| And the voiced / unvoiced sound discriminating unit 107
V / UV (voiced sound / unvoiced sound) discrimination data is supplied. The amplitude reevaluating unit 108 calculates the amplitude again for the band determined to be unvoiced (UV) by the voiced / unvoiced sound determining unit 107. The amplitude | A _m | _UV for this UV band is

[0053]

(Equation 4)

Is obtained by

The data from the amplitude reevaluating unit 108 is
Data number conversion (a kind of sampling rate conversion) unit 10
9 The data number conversion unit 109 is provided to make the number constant in consideration of the fact that the number of division bands on the frequency axis differs according to the pitch and the number of data (particularly the number of amplitude data) differs. is there. That is, for example, when the effective band is up to 3400 Hz , this effective band is divided into 8 to 63 bands according to the pitch, and the amplitude | A obtained for each of these bands is obtained.
The number m _MX +1 of _m | (including the amplitude of the UV band | A _m | _UV ) data also changes from 8 to 63. Therefore, the data number conversion unit 109 converts the variable number m _MX +1 of amplitude data into a fixed number N _C (for example, 44) data.

Here, in the present apparatus, dummy data for interpolating values from the last data in a block to the first data in a block is used for the amplitude data of one effective band on the frequency axis. After adding to increase the number of data to N _F , the band-limited K _OS times (for example, 8
Obtain an amplitude data of K _OS times the number by performing oversampling multiplied), the K _OS times the number ((m _MX +
1 ) × K _OS amplitude data is linearly interpolated and expanded to a larger number of N _M (eg, 2048), and the N _M data are thinned out to reduce the above-mentioned fixed number N _C (eg, 44). Convert to data.

The data (the fixed number N _C of amplitude data) from the data number conversion unit 109 is sent to the vector quantization unit 110, and is grouped into a predetermined number of data to form a vector. Will be applied. The quantized output data from the vector quantizer 110 is output to an output terminal 1
11 is taken out. The high-precision (fine) pitch data from the high-precision pitch search unit 106 is encoded by a pitch encoding unit 115 and output from an output terminal 11.
2 to be taken out. Further, the voiced / unvoiced sound (V / UV) discrimination data from the voiced / unvoiced sound discriminating unit 107 is extracted via an output terminal 113. Data from each of these output terminals 111 to 113 is transmitted as a signal of a predetermined transmission format.

Each of these data is obtained by processing the data in the block of N samples (for example, 256 samples), and the block is represented on the time axis by the frame of L samples. , The data to be transmitted is obtained in the frame unit. That is, the pitch data, V / UV discrimination data, and amplitude data are updated in the frame cycle.

Next, a synthesizing side (decoding side) for synthesizing an audio signal based on the respective data obtained by transmission.
Will be described with reference to FIG. In FIG. 9, the input terminal 121 has the amplitude data subjected to the vector quantization, the input terminal 122 has the encoded pitch data, and the input terminal 123 has the V data.
/ UV discrimination data is supplied. Input terminal 12
1 from the inverse vector quantizer 12
4 to be inversely quantized, and then sent to a data number inverse converter 125 for inverse conversion. The obtained amplitude data is sent to a voiced sound synthesizer 126 and an unvoiced sound synthesizer 127. The encoded pitch data from the input terminal 122 is input to the pitch decoding unit 1
28, and sent to the data number inverse conversion unit 125, the voiced sound synthesis unit 126, and the unvoiced sound synthesis unit 127. The V / UV discrimination data from input terminal 123 is sent to voiced sound synthesis section 126 and unvoiced sound synthesis section 127.

The voiced sound synthesizing section 126 has, for example, a cosine (cosin
e) A voiced sound waveform on the time axis is synthesized by wave synthesis, and the unvoiced sound synthesis unit 127 synthesizes an unvoiced sound waveform on the time axis by filtering, for example, white noise with a band-pass filter. The unvoiced sound synthesized waveform is added and synthesized by the adder 129 and extracted from the output terminal 130. In this case, the amplitude data, the pitch data, and the V / UV discrimination data are updated and provided every frame (L samples, for example, 160 samples) at the time of the analysis, but the continuity between the frames is improved (smoothness). For example, each value of the amplitude data and the pitch data is set as a data value at, for example, a center position in one frame, and each data value up to the center position of the next frame (one frame at the time of synthesis) is interpolated. Ask by That is,
In one frame at the time of synthesis (for example, from the center of the analysis frame to the center of the next analysis frame), each data value at the leading sample point and the end point (the leading edge of the next combined frame)
Each data value at a sample point is given, and each data value between these sample points is obtained by interpolation.

Hereinafter, the synthesis processing in the voiced sound synthesis section 126 will be described in detail. The one synthesized frame (L samples, for example, 160 samples) on the time axis in the m-th band (m-th harmonic band) determined as V (voiced sound)
Assuming that a voiced sound of a minute is V _m (n), using a time index (sample number) n in this synthesized frame, V _m (n) = A m (n) cos (θm (n)) 0 ≦ n < L (9) The final voiced sound V (n) is synthesized by adding (ΣV _m (n)) the voiced sounds of all the bands determined as V (voiced sound) in all the bands.

A _m (n) in the equation (9) is the amplitude of the m-th harmonic interpolated from the top to the end of the composite frame. In the simplest case, the value of the m-th harmonic of the amplitude data updated for each frame may be linearly interpolated.
That is, the m-th position at the end (n = 0) of the composite frame
The amplitude value of the harmonic is A _0m , and the end of the synthesized frame (n =
When the amplitude value of the m-th harmonic at the end of the next synthesized frame is A _Lm , A _m (n) = (Ln) A _0m / L + nA _Lm / L (10) A _m (n) may be calculated.

Next, the (9) phase theta _m (n) in the expression by _{θ m (m) = mω O1} n + n 2 m (ω L1 -ω 01) / 2L + φ 0m + Δωn ··· (11) You can ask. In this equation (11), φ _0m represents the phase of the m-th harmonic (frame initial phase) at the leading end (n = 0) of the combined frame, and ω 01 represents the basic value at the leading end (n = 0) of the combined frame. The angular frequency ω _L1 indicates the basic angular frequency at the end of the combined frame (n = L: the leading end of the next combined frame). Δω in the above equation (11) is
The minimum Δω is set so that the phase φ _{Lm at} n = L becomes equal to θ _m (L).

The method of obtaining the amplitude A _m (n) and the phase θ _m (n) according to the V / UV discrimination result when n = 0 and n = L in an arbitrary m-th band will be described below. I do. In the case where the m-th band is V (voiced sound) for both n = 0 and n = L, the amplitude Am (n) is obtained by calculating the transmitted amplitude values A0m and ALm according to the above-described equation (10). Linear interpolation and amplitude A
_m (n) may be calculated. The phase θ _m (n) is n = 0 and θ
Δω is set so that θ _m (L) becomes φ _Lm when _m (0) = φ _0m and n = L.

Next, when n = 0, V (voiced sound) and n =
If L (unvoiced sound) at L, the amplitude A _m (n)
Is linearly interpolated so that 0 A _m (L) from the transmission amplitude value A _{0 m} of A _m (0). The transmission amplitude value A _Lm at n = L is the amplitude value of the unvoiced sound, and is used in unvoiced sound synthesis described later. Phase θ _m (n) is set to _{θ m (0) = φ 0m} , and [Delta] [omega =
Set to 0.

Further, when n = 0, UV (unvoiced sound)
If V = voiced sound when n = L, the amplitude _Am
(n) sets the amplitude A _m (0) at n = 0 to 0 and performs linear interpolation so that the transmitted amplitude value A _Lm at n = L. Phase θ
The _m (n), the phase theta _m as (0) at n = 0, by using the phase value phi _Lm at the frame _{end, θ m (0) = φ} Lm -m (ω O1 + ω L1) L / 2 (12) and Δω = 0.

When both n = 0 and n = L are V (voiced sound), Δω is adjusted so that θ _m (L) becomes φ _Lm.
The method for setting is described. In the above equation (11), n
= By placing the _{L, θ m (L) =} mω O1 L + L 2 m (ω L1 -ω 01) / 2L + φ 0m + ΔωL = m (ω O1 + ω L1) L / 2 + φ 0m + ΔωL = φ Lm becomes, organize this Then, [Delta] [omega is, Δω = (mod2π ((φ Lm -φ 0m) - and _{mL (ω O1 + ω L1)} / 2) / L a (13) this equation (13) in mod2π (x). Is the main value of x
This function returns a value between π and + π. For example, x = 1.3
mod2π (x) = -0.7π when π, mod2 when x = 2.3π
When π (x) = 0.3π, x = -1.3π, mod2π (x) = 0.7
π, and so on.

FIG. 10A shows an example of the spectrum of an audio signal. Bands (harmonic numbers) m of 8, 9, and 10 are set to UV (unvoiced sound) and other bands are set to UV (unvoiced sound). Is V (voiced sound). This V
The time axis signal of the (voiced sound) band is the voiced sound synthesis unit 1
26, and the time axis signal of the UV (unvoiced sound) band is synthesized by the unvoiced sound synthesis unit 127.

Hereinafter, the unvoiced sound synthesizing process in the unvoiced sound synthesizing section 127 will be described. The waveform of the white noise signal on the time axis from the white noise generator 131 is windowed with an appropriate window function (for example, a Hamming window) with a predetermined length (for example, 256 samples), and the STFT (short circuit) is performed by the STFT processing unit 132. By performing (term Fourier transform) processing, a power spectrum on the frequency axis of white noise as shown in FIG. 10B is obtained. The power spectrum from the STFT processing unit 132 is sent to the band amplitude processing unit 133, and as shown in FIG. 10C, the amplitudes of the UV (unvoiced) bands (for example, m = 8, 9, 10) _Am | _UV is multiplied, and the amplitude of the other V (voiced sound) band is set to zero. The band amplitude processing section 133 is supplied with the amplitude data, the pitch data, and the V / UV discrimination data. The output from the band amplitude processing unit 133 is sent to the ISTFT processing unit 134, and the phase is converted to a signal on the time axis by performing inverse STFT processing using the phase of the original white noise. The output from the ISTFT processing unit 134 is output to an overlap adding unit 135.
And repeats the overlap and addition while weighting appropriately (to restore the original continuous noise waveform) on the time axis to synthesize a continuous time axis waveform. The output signal from the overlap adding unit 135 is sent to the adding unit 129.

As described above, the respective signals of the voiced sound portion and the unvoiced sound portion that have been synthesized in the synthesis portions 126 and 127 and returned on the time axis are added by the addition portion 129 at an appropriate fixed mixing ratio. The reproduced audio signal is extracted from the output terminal 130.

The components on the voice analysis side (encoding side) in FIG. 4 and the configuration on the voice synthesis side (decoding side) in FIG. 9 are described in terms of hardware. ) Can be realized by a software program.

As described above, in the MBE to which the pitch extraction method according to the present invention is applied, the pitch extraction in the pitch extraction unit 103 detects the peak level of the signal of each unit (each sub-block) obtained by subdividing the block, and the like. When the difference between the peak levels of each of these sub-blocks is large, the clip level is changed stepwise or continuously within the block, so that even if the peak level fluctuates rapidly, the pitch can be surely adjusted. Can be extracted.

The pitch extraction method according to the present invention is not limited to the above embodiment, and the high efficiency coding method applied is not limited to the above MBE.

[0074]

According to the pitch extracting method of the present invention, an input audio signal is extracted in units of a block, the block is divided into a plurality of sub-blocks, and a center clipped signal is extracted according to the peak level of each sub-block. By changing the clipping level for each block, reliable pitch extraction becomes possible.

Further, the pitch extracting method according to the present invention extracts an input audio signal in units of blocks and divides the input audio signal into a plurality of sub-blocks. By changing the clip level, it is possible to extract a reliable pitch even when the peak level fluctuates rapidly, such as when the sound rises or falls.

[Brief description of the drawings]

FIG. 1 is a functional block diagram of a pitch extraction method according to the present invention.

FIG. 2 is a flowchart illustrating an operation of a pitch extraction method according to the present invention.

FIG. 3 is a waveform diagram for explaining a pitch extraction method according to the present invention.

FIG. 4 is a functional block diagram showing a schematic configuration of an analysis side (encoding side) of a speech signal synthesis analysis encoding apparatus as a specific example of an apparatus to which the pitch extraction method according to the present invention is applied;

FIG. 5 is a diagram for explaining windowing processing.

FIG. 6 is a diagram for explaining a relationship between a windowing process and a window function.

FIG. 7 is a diagram showing time axis data as an object of orthogonal transform (FFT) processing.

FIG. 8 is a diagram showing spectrum data on a frequency axis, a spectrum envelope (envelope), and a power spectrum of an excitation signal.

FIG. 9 is a functional block diagram showing a schematic configuration of a synthesis side (decoding side) of a speech signal synthesis analysis encoding apparatus as a specific example of an apparatus to which the pitch extraction method according to the present invention is applied.

FIG. 10 is a diagram for explaining unvoiced sound synthesis when synthesizing an audio signal.

FIG. 11 is a waveform chart for explaining a conventional pitch extraction method.

[Explanation of symbols]

 Reference numeral 10: Block extraction processing unit 11: Clipping level setting unit 12: Center clip processing unit 13: Autocorrelation calculation unit 14: Pitch calculation unit 15 ····· Sub-block division processing unit ········································································································································································ / ······· / ······················································································· lip −and /

Claims (2)

(57) [Claims] 1. A pitch extracting method for extracting an input audio signal waveform in block units, center-clipping an audio signal waveform in the block, and extracting a pitch based on the center-clipped signal. A clip level is obtained for each of the sub-blocks, and a clipping level in the block is changed based on the clip level at the time of center clipping. 2. A peak level in the plurality of sub-blocks is determined as the clip level, and when a fluctuation of the peak level is larger than a predetermined value, a clipping level at the time of center clip is determined based on the clip level. 2. The pitch extracting method according to claim 1, wherein the pitch is changed within the block.