JP3398968B2 - Speech analysis and synthesis method - Google Patents

Description

Detailed Description of the Invention

[0001]

The present invention relates to a sound Koego formed method applied to the analysis synthesizing the speech signal coding apparatus.

[0002]

2. Description of the Related Art Human hearing is a kind of spectrum analyzer, and has the property of being heard as the same sound if the power spectra are equal. A method of obtaining a synthetic voice by utilizing this property is a voice analysis / synthesis method.

In order to obtain the above-mentioned synthesized sound, the analysis side analyzes the input voice signal, extracts or detects pitch information, voiced / unvoiced sound discrimination information, amplitude information, etc., transmits them to the synthesis side, and transmits them to the synthesis side. A voice is artificially created based on such information. In particular, the synthesizing side can be classified into a recording editing method, a parameter editing method, a rule synthesizing method, etc. depending on the synthesizing method.

In the above recording / editing system, the voice generated by a person is previously accumulated (recorded) in units of words, phrases, etc., read out as needed, and connected (edited),
It synthesizes voice.

The above-mentioned parameter editing system uses words, phrases, etc. as a unit as in the case of the above-mentioned recording editing system. However, the voice uttered by a person is analyzed in advance based on the voice generation model to form the parameter time series. In this method, a voice synthesizing device is driven by using a parameter time series which is stored as described above and is connected as needed, to synthesize a voice.

The rule synthesizing method is a technique for continuously converting a sequence represented by discrete symbols such as characters and phonetic symbols. In the process of conversion, universal and artificial properties of speech production are applied as synthesis rules.

In each of the above synthesis methods, the vocal tract characteristic is simulated in some form, and a synthesized sound is obtained by using a signal having substantially the same spectrum as the sound source wave.

[0008]

By the way, in the above speech analysis / synthesis method, it is necessary to match the phase on the synthesis side with the phase on the analysis side. In this case, when obtaining phase information on the combining side, linear prediction by angular frequency and correction by white noise may be used. However, control of noise (error) due to the true value of the phase and prediction is impossible with the white noise.

Further, since the level of white noise is changed and used as a correction term at a ratio of unvoiced sound in the entire band,
When blocks containing a lot of voiced sound are consecutive, no correction is made only by prediction. As a result, when a strong vowel lasts for a long time, errors accumulate and sound quality deteriorates.

[0010] Accordingly, the present onset Ming, an object of the present invention to provide a sound Koego forming method for realizing the sound quality improvements in the use of the noise that it is possible to control the large can and dispersion to correct the prediction.

[0011]

Means for Solving the Problems] sound Koego forming method according to the present invention divides an input audio signal in units of frames, determine the pitch for each frame that is classified, the fundamental wave of the determined pitch and in sound Koego forming method of synthesizing speech using a signal group representing the harmonics, and setting the phase of the frame front end of the fundamental wave and its harmonics to a predetermined value, the fundamental wave and its harmonics frame tip a phase in frame termination section of the wave, which is set to the predetermined value
The step of predicting based on the phase in the part, and the step of correcting the phase of the predicted frame end part by adding a correction term according to the frequency of the fundamental wave and its harmonics Solve.

Further, in the sound Koego forming method according to the present invention, said modifications may generate a random number having different dispersions in accordance with the frequency of the fundamental wave and harmonics, generated values above random number upper Symbol predicted frame termination of the phase
Correct by adding to.

[0013]

Sound Koego forming method according to the present invention, sets the phase of the fundamental wave and the frame tip portion of its harmonics of the pitch obtained by dividing the input speech signal in frame units to a predetermined value, The phase at the end of the frame of the fundamental wave and its harmonics, the frame ahead set to the predetermined value
Prediction is performed based on the phase at the end, and the predicted phase at the frame end is added to the correction term corresponding to the frequencies of the fundamental wave and its harmonics to make a correction .

[0014]

EXAMPLES Hereinafter, the sound Koego forming method according to the present invention, a specific example of applying the analysis-synthesis speech signal coding apparatus (so-called vocoder) will be described with reference to the drawings. This analysis-synthesis coding apparatus performs modeling that a voiced sound (Voiced) section and an unvoiced sound (Unvoiced) section exist in the frequency domain at the same time (in the same block or frame).

FIG. 1 is a diagram showing the overall schematic construction of an embodiment in which the present invention is applied to the above-mentioned speech signal analysis / synthesis coding apparatus. In this Figure 1, an embodiment of the sound Koego forming method according to the present invention, the analyzing unit 10 for analyzing the pitch information and the like from the input speech signal, various kinds of information transmitted by the transmission unit 2 from the analyzer 10 ( And a voiceless sound based on the pitch information and the like, and a synthesis unit 20 that synthesizes the voiced sound and the unvoiced sound.

The analyzing unit 10 extracts a voice signal input from the input terminal 1 in block units of a predetermined number of samples (N samples), and an input voice signal for each block from the block extracting unit 11. From this, a pitch information extraction unit 12 for extracting pitch information, a data conversion unit 13 for obtaining data converted on the frequency axis from the input voice signal for each block from the block extraction unit 11, and this data conversion unit 13 Band division section 14 for dividing the data on the frequency axis into a plurality of bands based on the pitch information of the pitch information extraction section 12, and power (amplitude) information and voiced sound V for each band of the band division section 14. Amplitude information & V / U for determining whether unvoiced sound UN
The V discrimination information detection unit 15 is included.

The synthesizing unit 20 has the pitch information, V / UV, transmitted from the analyzing unit 10 by the transmitting unit 2.
Upon receiving the discrimination information and the amplitude information, the voiced sound synthesis unit 21 synthesizes the voiced sound with the unvoiced sound synthesis unit 27, the synthesized voiced sound and unvoiced sound are added and synthesized by the addition unit 28, and the synthesized sound signal is obtained. It is taken out from the output terminal 3.

The above-mentioned respective information is obtained by processing the data in the block of N samples (for example, 256 samples), but the block represents the frame of L samples on the time axis. Since the data advances in units, the data to be transmitted is obtained in the above frame units. That is, pitch information, V
/ UV discrimination information and amplitude information will be updated.

The voiced sound synthesizing section 21 predicts the frame end phase (the phase of the leading edge of the next synthesized frame) based on the pitch information and the frame initial phase supplied from the input terminal 4, and , The phase predictor 22
Based on the corrected phase information from the phase correction unit 24 and the phase correction unit 24 that corrects the prediction from the above using the correction term from the noise adding unit 23 to which the pitch information and the V / UV discrimination information are supplied. The sine wave generator 25 reads out and outputs a sine wave from a sine wave ROM (not shown), and an amplitude amplifier 26 that is supplied with the amplitude information and amplifies the amplitude of the sine wave from the sine wave generator 25.

The unvoiced sound synthesizer 27 is supplied with the pitch information, V / UV discrimination information and amplitude information. For example, white noise is filtered by a band pass filter (not shown) to synthesize an unvoiced sound waveform on the time axis. There is.

In the adding section 28, the voiced sound synthesizing section 2 is used.
1. The voiced sound and unvoiced sound signals synthesized by the unvoiced sound synthesizer 27 are added at an appropriate fixed mixing ratio. Then, the added audio signal is output from the output terminal 3 as an audio signal.

Here, the voiced sound synthesizer 2 of the synthesizer 20 is used.
In the phase prediction unit 22 within 1, the time 0 (the beginning of the frame)
The phase of m-th harmonic (initial frame phase) at ψ _0m
Then, the phase ψ _Lm at the end of the frame is predicted as ψ _Lm = ψ _0m + m (ω _O1 + ω _L1 ) L / 2 (1). The phase φ _{m of} each band is φ _m = φ _Lm + ε _m (2) (1), (2) wherein L is the frame interval, Omegao1 the fundamental angular frequency at the tip of the composite frame (n = 0), omega _L1 is the composite frame termination (n = L: The following synthetic The fundamental angular frequency at the frame tip), ε _m , indicates the prediction correction term for each band.

From the equation (1), the phase predictor 22
Calculates the phase obtained by multiplying the average angular frequency of the mth harmonic by the time and adding the initial phase of the mth harmonic as the predicted phase at the time L. Further, from the above formula (2), the phase φ _{m of} each band is a value obtained by adding the prediction correction term ε _m to the above-mentioned predicted phase.

The predictive correction term ε _m has a random distribution among the bands (random), and random numbers can be used, but Gaussian noise is used in this embodiment. As shown in FIG. 2, this Gaussian noise is a noise in which the dispersion increases as the frequency becomes higher (eg, ε ₁ to ε ₁₀ ) in each band. This Gaussian noise properly approximates the error between the true value of the phase and the predicted value.

[0025] Here, now, if that dependency as shown in FIG. 2 is proportional to m for simplicity band, the predicted correction terms epsilon _m is, εm = h1 N (0, ki) ··· ( 3) is indicated. Here, h ₁ is a constant, k _i is a fraction, and 0 is an average.

Further, when the entire band is divided into two bands of voiced sound and unvoiced sound, if there are many unvoiced sound parts, the phase of each frequency component constituting the voice becomes more random,
The prediction correction term ε _m can be expressed as ε _m = h ₂ n _uj N (0, k _i ) ... (4). Where h ₂ is a constant, k _i is a fraction, 0 is an average, and n _uj is the number of unvoiced bands in block j.

In particular, when there is no disturbance in the distribution between the bands as described above, such as when the vowel of the input voice continues for a long time, or when the vowel changes to consonants and silence, the above (3), ( Since the predictive correction term expressed by the equation (4) rather deteriorates the sound quality of the synthesized speech, if delay is allowed, the amplitude information (power) S level one frame ahead or the decrease of the voiced sound portion is checked to find the above. Correction term ε _{m
The, ε m = h 3 max (} a, S j -S j + 1) N (0, k i) ··· (5) ε m = h 4 max (b, n vj -n v (j + 1 ₎ ) N (0, k _i ) ... (6) Here, a, b, h ₃ and h ₄ are constants.

Further, when the pitch information in the pitch information extraction unit 12 is low, the above correction term ε _m is set to ε _m = f in consideration of an increase in adverse effects due to increase of frequency bands and alignment of phases. (S _j , h _j ) N (0, k _i ) ... (7). Here, f is a frequency .

As described above, in the embodiment in which the present invention is applied to the speech signal analysis / synthesis coding apparatus, the noise used for the correction of the phase prediction is Gaussian to control the magnitude and variance thereof. .

[0030] Hereinafter, the sound Koego forming method according to the present invention, which is one type MBE synthesis analysis encoding unit of the audio signal (the so-called vocoder): A specific example of applying the (Multiband Excitation multi-band excitation) vocoders, the drawings Will be described with reference to. This MBE vocoder is based on DW Griffi
n and JS Lim, "Multiband Excitation Vocoder," IEE
E Trans. Acoustics, Speech, and Signal Processing, vo
L.36, No.8, pp.1223-1235, Aug.1988, the conventional PARCOR (PARtialauto-CORr
elation: Partial autocorrelation) In a vocoder or the like, a voiced sound section and an unvoiced sound section were switched for each block or frame when modeling speech, whereas in the MBE vocoder, the same time (in the same block or frame) Voiced section and unvoiced sound (Unvoice
d) It is modeled on the assumption that an interval and exists.

FIG. 3 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. 3, an audio signal is supplied to the input terminal 101, and the input audio signal is H
It is sent to a filter 102 such as a PF (high-pass filter) to remove a so-called DC (direct current) offset component and remove at least a low frequency component (200 Hz or less) for band limitation (for example, 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 extraction unit 103, the input voice signal data is divided into blocks in units of a predetermined number N (for example, N = 256) (or cut out by a rectangular window), and pitches of voice signals in this block are extracted. . Such cut-out block (256 samples) is used for L samples (for example, L = 16) as shown in A of FIG.
0) frame intervals are moved in the time axis direction, and the overlap between blocks is NL samples (for example, 9 samples).
6 samples). Also, the windowing processing unit 104
In this case, a predetermined window function, for example, a Hamming window is applied to 1 block N samples, and the windowed blocks are sequentially moved in the time axis direction at intervals of 1 frame L samples.

When this windowing process is expressed by a mathematical expression, x _w (k, q) = x (q) w (kL-q) (8) In this equation (8), k is a block number,
q represents the time index (sample number) of the data, and the q-th data x (q) of the input signal before processing is windowed by the window function (w (kL-q)) of the kth block. It is shown that the data x _w (k, q) can be obtained by doing so. FIG. 4A in the pitch extraction unit 103
The window function w _r (r) in the case of the rectangular window is as follows: w _r (r) = 1 0 ≦ r <N (9) = 0 r <0, N ≦ r window function w _h (r) in the case of Hamming window as shown in B of FIG. 4 is a section _{104, w h (r) =} 0.54
−0.46 cos (2πr / (N−1)) 0 ≦ r <N (10) = 0 r <0, N ≦ r. Such a window function w _r (r) or w (8) when using the _h (r) formula of the window function w (r) (= w (KL-
q)), the zero-zero section is: 0 ≦ kL−q <N, which is transformed into kL−N <q ≦ kL Therefore, for example, in the case of the above rectangular window, the window function w _r (kL-q) =
As shown in FIG. 5, 1 becomes kL-N <q ≦ kL.
It will be when. Further, the above equations (8) to (10) are expressed by the length N
It shows that the window of (= 256) samples advances by L (= 160) samples. Below, above (9)
N points (0 ≦ r
The non-zero sample sequences of <N) are respectively x _wr (k, r) and x _wh
We will denote it as (k, r).

In the windowing processing unit 104, as shown in FIG. 6, 179 is applied to the sample sequence x _wh (k, r) of 256 samples of one block on which the Hamming window of the above equation (10) is applied.
Two samples of 0 data are added (so-called zero padding) to form 2048 samples, and the orthogonal transformation unit 105 performs orthogonal transformation such as FFT (Fast Fourier Transform) on the time-axis data sequence of 2048 samples. Processing is performed.

In the pitch extraction unit 103, the above x _wr (k, r)
Pitch extraction is performed based on the sample sequence (1 block N samples). The pitch extraction method is known to include periodicity of a time waveform, periodic frequency structure of spectrum, and one using an autocorrelation function.
The center correlation waveform autocorrelation method is used. Regarding the center clip level in the block at this time, one clip level may be set for each block, but the peak level of the signal of each part (each sub-block) obtained by subdividing the block is detected and When there is a large difference in peak level between the sub-blocks, 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 this 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 for the data of N samples of one block), and the maximum peak of the plurality of peaks is equal to or larger than a predetermined threshold value. In the case of, the maximum peak position is set as the pitch cycle, and in other cases, the pitch is within the pitch range that satisfies a predetermined relationship with the pitch other than the current frame, for example, the pitch of the previous frame and the pitch of the previous frame. As a result, a peak in the range of ± 20% is obtained, and the pitch of the current frame is determined based on this peak position. In this pitch extraction unit 103, a relatively rough pitch search is performed by an open loop, and the extracted pitch data has a high precision (fine) pitch search unit 10.
6, the pitch search (pitch fine search) with high accuracy is performed by the closed loop.

High precision (fine) pitch search unit 106
Includes rough pitch data of integer (integer) values extracted by the pitch extraction unit 103, and the orthogonal transformation unit 10.
5, for example, FFT-processed data on the frequency axis is supplied. In this high precision pitch search unit 106,
Centering on the above coarse pitch data value, ± in increments of 0.2 to 0.5
Shake several samples at a time to reach the optimum fine pitch data value with a decimal point (floating). As a fine search method at this time, 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
Let S (j) as spectrum data on the frequency axis orthogonally transformed by T etc. be expressed as S (j) = H (j) | E (j) | 0 <j <J (11) It is assumed that the model. Where J is
Corresponding to ω _s / 4π , sampling frequency f _s = ω _s /
When 2π is, for example, 8 kHz, it corresponds to 4 kHz. In the above equation (11), spectrum data S on the frequency axis
When (j) has a waveform as shown in A of FIG. 7, H (j) shows the spectrum envelope (envelope) of the original spectrum data S (j) as shown in B of FIG. 7, and E ( j) is shown in FIG.
3 shows a spectrum of an excitation signal (excitation) which is cyclic at an equal level as shown in C of FIG. That is,
The FFT spectrum S (j) has a spectral envelope H
It is modeled as the product of (j) and the power spectrum of the excitation signal | E (j) |.

Power spectrum of the above excitation signal | E (j)
| Is a spectral waveform corresponding to the waveform of one band (band) for each band on the frequency axis in consideration of the periodicity (pitch structure) of the waveform on the frequency axis determined according to the pitch. It is formed by arranging it repeatedly. The waveform for one band is obtained by performing FFT by regarding a waveform obtained by adding (zero-filling) 0 data for 1792 samples to a Hamming window function of 256 samples as shown in FIG. 6 as a time axis signal. 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 above pitch, a value (a kind of amplitude) | A that represents the above H (j) (minimizes the error for each band) | A _m
Ask for |. Here, for example, when the lower limit point and the upper limit point 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

[0039]

[Equation 1]

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

[0041]

[Equation 2]

Therefore, when | A _m | in this equation (13),
Minimize the error ε _m . Such an amplitude | A _m | is obtained for each band, and the obtained amplitude | A _m | is used to obtain the error ε m for each band defined by the above equation (12). Next, the sum total value Σε _m of all the bands of the error ε _m for each band is obtained. Further, such an error sum value Σε _m of all bands is obtained for some slightly different pitches, and a pitch that minimizes the error sum value Σε _m is obtained.

That is, with the rough pitch obtained by the pitch extraction unit 103 as the center, several types are prepared up and down in steps of, for example, 0.25. The error sum value Σε _m is obtained for each of these plural kinds of slightly different pitches. In this case, if the pitch is determined, the bandwidth is determined, and from the above equation (13), the power spectrum | S (j) | of the data on the frequency axis and the excitation signal spectrum | E
(j) | can be used to obtain the error ε _m in the above equation (12), and the total sum value Σε _m of all the bands can be obtained. This error sum total value Σε _m is obtained for each pitch, and the pitch corresponding to the minimum error sum value is determined as the optimum pitch. As described above, the high-precision pitch search unit 106 finds the optimum fine (eg, 0.25 step) pitch, and the amplitude | A _m | corresponding to this optimum pitch.
Is determined.

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

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

[0046]

[Equation 3]

If this NSR value is larger than a predetermined threshold value (for example, 0.3) (error is large), | A _m || E (j) | due to | S (j) in that band It can be judged that the approximation of | is not good (the above excitation signal | E (j) | is unsuitable as a basis), and the band is UV (Unvoice
d, unvoiced sound). In other cases, it can be judged that the approximation has been performed to some extent, and the band is set to V
(Voiced, voiced sound).

Next, the amplitude re-evaluation unit 108 has the amplitude | A _m evaluated as the data on the frequency axis from the orthogonal transformation unit 105 and the fine pitch evaluated from the high precision pitch search unit 106.
| And each voiced sound / unvoiced sound discrimination unit 107
V / UV (voiced sound / unvoiced sound) discrimination data from is supplied. The amplitude re-evaluation unit 108 re-calculates the amplitude of the band determined as unvoiced sound (UV) by the voiced sound / unvoiced sound determination unit 107. The amplitude | A _m | _UV for this UV band is

[0049]

[Equation 4]

It is calculated by

The data from the amplitude re-evaluation unit 108 is
Data number conversion (a kind of sampling rate conversion) unit 10
Sent to 9. The data number conversion unit 109 is for making the number constant in consideration of the fact that the number of divided bands on the frequency axis differs according to the pitch and the number of data (especially the number of amplitude data) differs. is there. That is, for example, when the effective band is up to 3400 Hz , the effective band is divided into 8 bands to 63 bands according to the pitch, and the amplitude | A obtained for each of these bands | A
_{The number of m m} (including the UV band amplitude | A _m | _UV ) data m _MX +1 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) of data.

Here, in this embodiment, dummy data for interpolating values from the last data in the block to the first data in the block with respect to the amplitude data of one block of the effective band on the frequency axis. Is added to increase the number of data to N _F , and then the bandwidth-limited K _OS times (for example, 8
By multiplying the number of K _OS times the amplitude data, and multiplying the number of K _OS times (( m _MX +
1) amplitude data of × K _OS pieces) extended to linear interpolation to more NM number (e.g. 2048), the data of the N thinned out _M data the predetermined number N _C (e.g. 44) Convert to.

The data from the data number conversion unit 109 (the above-mentioned fixed number N _C of amplitude data) is sent to the vector quantization unit 110, and a predetermined number of data are collected into a vector, and vector quantization is performed. Is given. The quantized output data from the vector quantizer 110 is output to the output terminal 1
It is taken out via 11. Further, the high-precision (fine) pitch data from the high-precision pitch search unit 106 is coded by the pitch coding unit 115, and the output terminal 11
It is taken out via 2. Further, the voiced sound / unvoiced sound (V / UV) discrimination data from the voiced sound / unvoiced sound discrimination unit 107 is taken out through the output terminal 113. The data from these output terminals 111 to 113 are transmitted as signals in a predetermined transmission format.

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

Next, a synthesizing side (decoding side) for synthesizing a voice signal based on the above-mentioned respective data obtained by transmission.
The general configuration of will be described with reference to FIG. In FIG. 8, the vector-quantized amplitude data is input to the input terminal 121, the encoded pitch data is input to the input terminal 122, and the V-value is input to the input terminal 123.
/ UV discrimination data is supplied respectively. Input terminal 12
The quantized amplitude data from 1 is the inverse vector quantizer 12
4 is inversely quantized, is then transmitted to the data number inverse conversion unit 125 and is inversely converted, and the obtained amplitude data is transmitted to the voiced sound synthesis unit 126 and the unvoiced sound synthesis unit 127. The encoded pitch data from the input terminal 122 is the pitch decoding unit 1
It is decoded at 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 the input terminal 123 is sent to the voiced sound synthesis unit 126 and the unvoiced sound synthesis unit 127.

In the voiced sound synthesis unit 126, for example, cosine (cosin)
e) The voiced sound waveform on the time axis is synthesized by wave synthesis, and the unvoiced sound synthesis unit 127 synthesizes the unvoiced sound waveform on the time axis by filtering white noise, for example, with a bandpass filter, and synthesizes these voiced sound synthesized waveforms. The unvoiced sound synthesis waveform is added and synthesized by the addition unit 129 and is taken out from the output terminal 130. In this case, the amplitude data, the pitch data, and the V / UV discrimination data are updated and given for each frame (L sample, for example, 160 samples) at the time of the analysis, but the continuity between the frames is improved (smoothed). Therefore, each value of the amplitude data and the pitch data is set to each data value at, for example, the center position in one frame, and each data value up to the center position of the next frame (one frame at the time of composition) is interpolated. Ask by. That is,
In one frame at the time of synthesis (for example, from the center of the above analysis frame to the center of the next analysis frame), each data value at the tip sample point and the end (the tip of the next synthesis frame)
Each data value at the sample point is given, and each data value between these sample points is obtained by interpolation.

The synthesis process in the voiced sound synthesis unit 126 will be described in detail below. The one synthesized frame (L samples, eg, 160 samples) on the time axis in the m-th band (band of the m-th harmonic) determined to be V (voiced sound)
When the amount of voiced and V _m (n), using a time index (sample number) n in the synthetic _{frame, V m (n) = A} m (n) cos (θ m (n)) 0 ≦ n <L can be expressed as (16). The final voiced sound V (n) is synthesized by adding (ΣV _m (n)) the voiced sounds of all bands that are determined to be V (voiced sound) of all bands.

A _m (n) in the equation (16) is the amplitude of the m-th harmonic wave that is interpolated from the beginning to the end of the composite frame. The simplest way is to linearly interpolate the value of the m-th harmonic of the amplitude data updated in frame units.
That is, the m-th frame at the tip (n = 0) of the composite frame
The amplitude value of the harmonic is A _0m , the end of the composite frame (n =
L: the amplitude value of the m-th harmonic at the next composite frame) is A _Lm , then A _m (n) = (Ln) A _0m / L + nA _Lm / L ... (17) It suffices to calculate A _m (n).

Next, the phase θ _m (n) in the above equation (16) is given by θ _m (n) = mω _O1 n + n ² m (ω _L1 −ω ₀₁ ) / 2L + φ _{0 m} + Δω n (18) You can ask. In this equation (18), φ _0m represents the phase (frame initial phase) of the m-th harmonic at the top (n = 0) of the composite frame, and ω ₀₁ represents the top of the composite frame (n = 0). The fundamental angular frequency, ω _L1, indicates the fundamental angular frequency at the end of the composite frame (n = L: leading end of the next composite frame). Δω in the above equation (18) is
Set a minimum Δω such that the phase φ _{Lm at} n = L is equal to θ _m (L).

On the other hand, in the embodiment of the present invention, the phase is predicted and calculated on the combining side without sending φ0m + Δωn in the equation (18) to the combining side. That is, the phase prediction unit 2
2 is obtained by adding m (ω _O1 + ω _L1 ) L / 2 to the m-th harmonic phase (frame initial phase) ψ _0m at time 0 (the beginning of the frame) as shown in the above equation (1) The phase ψ _{Lm at} is predicted and calculated. Further, the phase φ _{m of} each band is shown by adding ε _m to the above-predicted and calculated phase ψ _Lm . This ε _m indicates the prediction correction term in each band. In the present invention, Gaussian noise is used for this prediction correction term ε _m .

Here, A of FIG. 9 shows an example of the spectrum of the voice signal, and the bands with band numbers (harmonics number) m of 8, 9, and 10 are UV (unvoiced sound), and the other bands. Is V (voiced sound). This V
The time axis signal of the (voiced sound) band is the voiced sound synthesis unit 1 described above.
26, and the time axis signal of the UV (unvoiced sound) band is synthesized by the unvoiced sound synthesis unit 127.

The unvoiced sound synthesizing process in the unvoiced sound synthesizing section 127 will be described below. The white noise signal waveform on the time axis from the white noise generation unit 131 is windowed by a suitable window function (for example, Hamming window) with a predetermined length (for example, 256 samples), and the STFT processing unit 132 performs STFT (short circuit). By performing the term Fourier transform) processing, a power spectrum of the white noise on the frequency axis as shown in B of FIG. 9 is obtained. The power spectrum from the STFT processing unit 132 is converted to the band amplitude processing unit 1
33, and as shown in FIG. 9C, the above-mentioned amplitude | A _m | _UV is multiplied with respect to the above-mentioned UV (unvoiced) band (for example, m = 8, 9, 10), and another V (voiced sound) is generated. ) Is set to 0. This band amplitude processing unit 1
The amplitude data, pitch data, and V / UV discrimination data are supplied to 33. The output from the band amplitude processing unit 133 is sent to the ISTFT processing unit 134, and the phase is converted into 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 sent to the overlap adding unit 135, which repeats overlap and addition while appropriately weighting (so that the original continuous noise waveform can be restored) on the time axis, and continuously. Time-domain waveforms are synthesized.
The output signal from the overlap adder 135 is sent to the adder 129.

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

[0064] Thus, the sound Koego forming method according to the present invention, in the specific example applied to MBE, it is possible to control the size and dispersion by a noise used to predict the phase of Gaussian.

Regarding the configuration on the speech analysis side (encoding side) in FIG. 3 and the configuration on the speech synthesis side (decoding side) in FIG. 7, although each unit is described in hardware, a so-called DSP (digital It is also possible to realize it by a software program using a signal processor or the like.

[0066]

Sound Koego forming method according to the present invention is, sets the phase of the fundamental wave and the frame tip portion of the harmonics of the input audio signal obtained by dividing a frame unit pitch to a predetermined value However, the phase of the fundamental wave and its harmonics at the frame end is set to the above-specified value.
The magnitude and variance of noise are predicted by correcting the phase of the frame end by adding the predicted phase of the frame end to a correction term corresponding to the frequencies of the fundamental wave and its harmonics. Can be controlled and the sound quality can be improved. Further, by using the signal level of the voice and its temporal change, it is possible to prevent the accumulation of errors and prevent the deterioration of the sound quality at the vowel or the transition point from the vowel part to the consonant part.

[Brief description of drawings]

1 is a functional block diagram of a specific example of applying the sound Koego forming method according to the present invention the so-called vocoder.

2 is a characteristic diagram for explaining a Gaussian noise for use in sound Koego forming method according to the present invention.

3 is a functional block diagram showing the schematic configuration of the analysis side of the analysis-by-synthesis speech signal coding apparatus as a specific example of device Sound Koego forming method according to the present invention is applied (encoding end).

FIG. 4 is a diagram for explaining a windowing process.

FIG. 5 is a diagram for explaining a relationship between windowing processing and a window function.

FIG. 6 is a diagram showing time axis data as an object of orthogonal transform (FFT) processing.

FIG. 7 is a diagram showing spectrum data on a frequency axis, a spectrum envelope (envelope), and a power spectrum of an excitation signal.

8 is a functional block diagram showing the schematic configuration of the synthesis side of synthesis analysis the speech signal coding apparatus as a specific example of device Sound Koego forming method according to the present invention is applied (decoding side).

FIG. 9 is a diagram for explaining unvoiced sound synthesis when synthesizing a voice signal.

─────────────────────────────────────────────────── ─── Continuation of the front page (56) Reference JP-A-58-23100 (JP, A) JP-A-64-28700 (JP, A) JP-A-3-139922 (JP, A) JP-A-2- 137900 (JP, A) JP 61-32094 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G10L 19/02 G10H 7/08

Claims (2)

(57) [Claims] 1. A sound for synthesizing a voice by dividing an input voice signal on a frame-by-frame basis, obtaining a pitch for each divided frame, and using a signal group representing a fundamental wave of the obtained pitch and its harmonics. in Koego forming method, and setting the position <br/> phase in the frame tip portion of the fundamental wave and its harmonics to a predetermined value, the phase at the frame end of the fundamental wave and its harmonics, the At the tip of the frame set to the specified value
And a step of correcting the predicted phase of the frame end portion by adding a correction term according to the frequencies of the fundamental wave and its harmonics. sound Koego forming method characterized. Wherein the step of modifying the generates a random number having different dispersions in accordance with the frequency of the fundamental wave and harmonics, the phase of the frame end portion that is above Symbol predict the occurrence values in the random number sound Koego forming method according to claim 1, wherein the modifying by addition.