Method for speech coding based on a code excited linear prediction (CELP) model

• US 6,073,092 A
• Filed: 06/26/1997
• Issued: 06/06/2000
• Est. Priority Date: 06/26/1997
• Status: Expired due to Term

• Current Assignee: Google Technology Holdings LLC (Alphabet Inc.)
• Original Assignee: Telogy Networks, Inc. (Texas Instruments, Inc.)
• Inventors: Kwon, Soon Y.
• Primary Examiner(s): MCFADDEN, SUSAN IRIS
• Application Number:
  US08/883,019
• Time in Patent Office: 1,076 Days
• Field of Search: 704/219, 704/222, 704/221, 704/220, 704/223, 704/262
• US Class Current: 704/219
• CPC Class Codes: G10L 19/12 the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
• CPC Class Codes: G10L 2019/0002 Codebook adaptations

Abstract

The invention provides a method for speech coding using Code-Excited Linear Prediction (CELP) producing toll-quality speech at data rates between 4 and 16 Kbit/s. The invention uses a series of baseline, implied and adaptive codebooks, comprised of pulse and random codebooks, with associated gain vectors, to characterize the speech. Improved quantization and search techniques to achieve real-time operation, based on the codebooks and gains, are also provided.

Claims

1. A method for speech coding based on a code excited linear prediction (CELP) model comprising:

(a) dividing speech at a sending station into discrete speech samples;

(b) digitizing the discrete speech samples;

(c) forming a mixed excitation function by selecting a combination of two codevectors from two fixed codebooks, each having a plurality of codevectors, and selecting a combination of two codebook gain vectors from a plurality of codebook gain vectors;

(d) selecting an adaptive codevector from an adaptive codebook, and selecting a pitch gain in combination with the mixed excitation function to represent the digitized speech;

(e) encoding one of the two selected codevectors, both of the selected codebook gain vectors, the adaptive codevector and the pitch gain as a digital data stream;

(f) sending the digital data stream from the sending station to a receiving station using transmission means;

(g) decoding the digital data stream at the receiving station to reproduce the selected codevector, the two codebook gain vectors, the adaptive codevector, the pitch gain, and LPC filter parameters;

(h) reproducing a digitized speech sample at the receiving station using the selected codevector, the two codebook gain vectors, adaptive codevector, the pitch gain, and the LPC filter parameters;

(i) converting the digitized speech sample at the receiving station into an analog speech sample; and

(j) combining a series of analog speech samples to reproduce the coded speech; and

wherein encoding one of the two selected codevectors, both of the selected codebook gain vectors, the adaptive codevector and pitch gain as a digital data stream further comprises;

adjusting the baseline codevector by the baseline gain and adjusting the implied codevector by the implied gain to form a mixed excitation function;

using the mixed excitation function as an input to a pitch filter;

using the output of the pitch filter as an input of a linear predictive coding synthesis filter; and

subtracting the output from the linear predictive coding synthesis filter from the speech to form an input to a weighting filter.

2. The method for speech coding based on a code excited linear prediction (CELP) model of claim 1 wherein the two fixed codebooks further comprise:

(a) selecting the first of the combination of two codevectors from a pulse codebook with a plurality of pulse codevectors; and

(b) selecting the second of the combination of two codevectors from a random codebook with a plurality of random codevectors.

3. The method for speech coding based on a code excited linear prediction (CELP) model of claim 1 wherein the two fixed codebooks further comprise:

(a) selecting the first of the combination of two codevectors from a baseline codebook with a plurality of baseline codevectors; and

(b) selecting the second of the combination of two codevectors from an implied codebook with a plurality of implied codevectors.

4. The method for speech coding based on a code excited linear prediction (CELP) model of claim 3 further comprising:

(a) selecting the implied codevector from a random codebook, which is within the baseline codebook and the implied codebook, when the baseline codevector is selected from the pulse codebook, and

(b) selecting the implied codevector from a pulse codebook, which is within the baseline codebook and within the implied codebook, when the baseline codevector is selected from the random codebook.

5. The method for speech coding based on a code excited linear prediction (CELP) model of claim 1 further comprising:

(a) representing the plurality of codevectors with a codebook index; and

(b) representing the adaptive codevector with an adaptive codebook index, wherein the indices and codebook gain vectors are encoded as the digital data stream.

6. The method for speech coding based on a code excited linear prediction (CELP) model of claim 1 further comprising:

(a) providing an implied codebook for at least one of the fixed codebooks, wherein the implied codebook further comprises;

(b) providing an encoder means; and

(c) providing a decoder means.

7. The method for speech coding based on a code excited linear prediction (CELP) model of claim 6 wherein the encoder means further comprises:

(a) high pass filtering the speech;

(b) dividing the speech into frames of speech;

(c) providing autocorrelation calculation of the frames of speech;

(d) generating prediction coefficients from the speech samples using linear prediction coding analysis;

(e) bandwidth expanding the prediction coefficients;

(f) transforming the bandwidth expanded prediction coefficients into line spectrum pair frequencies;

(g) transforming the line spectrum pair frequencies into line spectrum pair residual vectors;

(h) split vector quantizing the line spectrum pair residual vectors;

(i) decoding the line spectrum pair frequencies;

(j) interpolating the line spectrum pair frequencies;

(k) converting the line spectrum pair frequencies to linear coding prediction coefficients;

(l) extracting pitch filter parameters from the frames of speech;

(m) encoding the pitch filter parameters; and

(n) extracting mixed excitation function parameters from the baseline codebook and the implied codebook.

8. The method for speech coding based on a code excited linear prediction (CELP) model of claim 7 wherein split vector quantizing the line spectrum pair residual vectors further comprises:

(a) separating the line spectrum pair residual vectors into a low group and a high group;

(b) removing bias from the line spectrum pair residual vectors;

(c) calculating a residual for each line spectrum pair residual vector with a moving average predictor and a quantizer; and

(d) generating a line spectrum pair transmission code as an output from the quantizer.

9. The method for speech coding based on a code excited linear prediction (CELP) model of claim 7 wherein decoding the line spectrum pair frequencies further comprises:

(a) dequantizing the line spectrum pair residual vectors;

(b) calculating zero mean line spectrum pairs from the dequantized line spectrum pair residual vectors; and

(c) adding bias to the zero mean line spectrum pairs to form the line spectrum pair frequencies.

10. The method for speech coding based on a code excited linear prediction (CELP) model of claim 7 wherein extracting pitch filter parameters from the frames of speech further comprises:

(a) providing a zero input response;

(b) providing a perceptual weighting filter;

(c) subtracting the zero input response from the speech to form an input to the perceptual weighting filter;

(d) providing a target signal, which further comprises the output from the perceptual weighting filter;

(e) providing a weighted LPC filter;

(f) adjusting the adaptive codevector by the adaptive gain to form an input to the weighted LPC filter;

(g) determining the difference between the output from the weighted LPC filter and the target signal;

(h) finding the mean squared error for all possible combinations of adaptive codevector and adaptive gain; and

(i) selecting the adaptive codevector and adaptive gain that correlate to the minimum mean squared error as the pitch filter parameters.

11. The method for speech coding based on a code excited linear prediction (CELP) model of claim 7 wherein extracting mixed excitation function parameters further comprises:

(a) subtracting a zero input response of a pitch filter from the speech to form an input to a perceptual weighting filter;

(b) generating a target signal, which comprises the output from the perceptual weighting filter;

(c) adjusting the baseline codevector with the baseline gain and adjusting the implied codevector with the implied gain to form the mixed excitation function;

(d) using the mixed excitation function as an input to a weighted LPC filter;

(e) determining the difference between the output of the weighted LPC filter and the target signal;

(f) finding the mean squared error for all possible combinations of baseline codevector, baseline gain, implied codevector and implied gain; and

(g) selecting the baseline codevector, baseline gain, implied codevector and implied gain based on the minimum mean squared error as the mixed excitation parameters.

12. The method for speech coding based on a code excited linear prediction (CELP) model of claim 6 wherein the decoder means further comprises:

(a) generating the mixed excitation function from the baseline codebook and the implied codebook using the selected baseline codevector and implied codevector;

(b) generating an input to a linear predictive coding synthesis filter from the mixed excitation function and the adaptive codebook using the selected adaptive codevector;

(c) calculating an implied codevector from the output of the linear predictive coding synthesis filter;

(d) providing feedback of the calculated pitch filter output to the adaptive codebook;

(e) post filtering the output from the linear predictive coding synthesis filter; and

(f) producing a perceptually weighted speech from the post filtered output.

13. A method for speech coding based on a code excited linear prediction (CELP) model comprising:

(a) dividing speech at a sending station into discrete speech samples;

(b) digitizing the discrete speech samples;

(c) forming a mixed excitation function by selecting a combination of two codevectors from two fixed codebooks, each having a plurality of codevectors, and selecting a combination of two codebook gain vectors from a plurality of codebook gain vectors;

(d) selecting an adaptive codevector from an adaptive codebook, and selecting a pitch gain in combination with the mixed excitation function to represent the digitized speech;

(e) encoding one of the two selected codevectors, both of the selected codebook gain vectors, the adaptive codevector and the pitch gain as a digital data stream;

(f) sending the digital data stream from the sending station to a receiving station using transmission means;

(g) decoding the digital data stream at the receiving station to reproduce the selected codevector, the two codebook gain vectors, the adaptive codevector, the pitch gain, and LPC filter parameters;

(h) reproducing a digitized speech sample at the receiving station using the selected codevector, the two codebook gain vectors, adaptive codevector, the pitch gain, and the LPC filter parameters;

(i) converting the digitized speech sample at the receiving station into an analog speech sample; and

(j) combining a series of analog speech samples to reproduce the coded speech wherein the two fixed codebooks further comprise;

selecting the first of the combination of two codevectors from a baseline codebook with a plurality of baseline codevectors; and

selecting the second of the combination of two codevectors from an implied codebook with a plurality of implied codevectors,

wherein reproducing a digitized speech sample at the receiving station using the selected codevector, the two codebook gain vectors, adaptive codevector, the pitch gain, and the LPC filter parameters further comprises;

adjusting the baseline codevector by the baseline gain and adjusting the implied codevector by the implied gain to form the mixed excitation function;

using the mixed excitation function as an input to a pitch filter;

using the output from the pitch filter as an input to an LPC filter;

postfiltering the output of the LPC filter; and

producing a digitized speech sample from the output from the LPC filter.

14. The method for speech coding based on a code excited linear prediction (CELP) model of claim 14 wherein post filtering the output of the LPC filter further comprises:

(a) inverse filtering the output of the LPC filter with a zero filter to produce a residual signal;

(b) operating on the residual signal outpt of the zero filter with a pitch post filter;

(c) operating on the output of the pitch post filter with an all-pole filter;

(d) operating on the output of the all-pole filter with a tilt compensation filter to generate post-filtered speech;

(e) operating on the output of the tilt compensation filter with a gain control to match the energy of the postfilter input; and

(f) operating on the output of the gain control with a highpass filter to produce perceptually enhanced speech.

15. A method of encoding a speech signal comprising:

adjusting a baseline codevector by a baseline gain and adjusting an implied codevector by an implied gain to form a mixed excitation function;

using the mixed excitation function as an input to a pitch filter;

using the output of the pitch filter as an input of a linear predictive coding synthesis filter; and

producing an encoded speech signal based on an output of the predictive coding synthesis filter.

16. The method of claim 15, further comprising subtracting an output from the linear predictive coding synthesis filter from the speech signal to form an input to a weighting filter.

17. The method of claim 16, wherein the speech signal comprises digitized speech produced by digitizing discrete speech samples.

18. The method of claim 17, wherein the mixed excitation function is formed by selecting a combination of two codevectors from two fixed codebooks, each having a plurality of codevectors, and selecting a combination of two codebook gain vectors from a plurality of codebook gain vectors.

19. The method of claim 18, further comprising selecting an adaptive codevector from an adaptive codebook, and selecting a pitch gain in combination with the mixed excitation function to represent the digitized speech.

20. The method of claim 19, further comprising encoding one of the two selected codevectors, both of the selected codebook gain vectors, the adaptive codevector and the pitch gain as a digital data stream.

21. A method for speech coding comprising:

forming a mixed excitation function by selecting a first of a combination of codevectors from a baseline codebook having a plurality of baseline codevectors and by selecting a second of the combination of codevectors from an implied codebook having a plurality of implied codevectors;

extracting mixed excitation function parameters from the baseline codebook and the implied codebook; and

producing an encoded speech signal based on the mixed excitation function parameters.

22. The method of claim 21, further comprising selecting a combination of two codebook gain vectors from a plurality of codebook gain vectors.

23. The method of speech coding of claim 22, further comprising encoding one of the selected codevectors, both of the selected codebook gain vectors, the adaptive codevector, and the pitch gain as a digital data stream.

24. The method of speech coding of claim 21, further comprising selecting an adaptive codevector from an adaptive codebook, and selecting a pitch gain in combination with the mixed excitation function to represent the digitized speech.