Speech coding method and apparatus using mean squared error modifier for selected speech coder parameters using VSELP techniques

• US 5,692,101 A
• Filed: 11/20/1995
• Issued: 11/25/1997
• Est. Priority Date: 11/20/1995
• Status: Expired due to Term

• Current Assignee: Blackberry Limited
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Jasiuk, Mark A., Gerson, Ira A., Hartman, Matthew A.
• Primary Examiner(s): MacDonald, Allen R.
• Assistant Examiner(s): Chawan, Vijay B.
• Application Number:
  US08/560,857
• Time in Patent Office: 736 Days
• Field of Search: 395/2.28, 395/2.34, 395/2.38, 395/2.09, 395/2.16, 395/2.31, 395/2.32, 395/2.1
• US Class Current: 704/222
• 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 2019/0014 Selection criteria for distances

Abstract

An improved speech coder provides a more natural sounding replication of speech by modifying the mean-squared error criterion for the selected speech coder parameters. Specifically, the modification emphasizes the signal components that the speech coder has difficulty matching, i.e. the high frequencies. This emphasis is constrained to certain limitations to avoid over-emphasizing the speech.

Claims

1. A method of matching energy of speech coding vectors to an input speech vector comprising the steps of:

choosing a codevector to represent the input speech vector;

optimizing a long term predictor coefficient and a gain term for the codevector, thereby forming an optimized long term predictor and an optimized gain term; and

determining a gain bias factor to more closely match an energy of the code vector to an energy of the input speech vector; and

altering the optimal long term predictor coefficient and the optimal gain term using the gain bias factor.

2. The method of claim 1 wherein the step of determining a gain bias factor further comprises the steps of:

forming a synthetic excitation signal using the codevector, the optimal long term predictor and the optimal gain term;

calculating the energy of the input speech vector, forming a speech data energy value;

calculating the energy of the synthetic excitation signal, forming a synthetic excitation energy value;

calculating a ratio of the speech data energy value and the synthetic excitation energy value; and

determining the square root of the ratio, forming the gain bias factor.

3. The method of claim 2 wherein the step of determining a gain bias factor further comprises the step of limiting the ratio value between an upper bound and a lower bound.

4. The method of claim 2 wherein the step of altering further comprises:

adjusting the input speech vector by the gain bias factor, thereby forming an adjusted input speech vector; and

quantizing the optimal long term predictor coefficient and the optimal gain term to minimize the error between the adjusted input speech vector and the synthetic excitation signal.

5. A method of speech coding comprising the steps of:

receiving a speech data signal;

providing excitation vectors in response to said step of receiving;

determining an excitation gain coefficient and a long term predictor coefficient for use by a long term predictor filter and a Pth-order short term predictor filter;

filtering said excitation vectors utilizing said long term predictor filter and said short term predictor filter, forming filtered excitation vectors;

comparing said filtered excitation vectors to said speech data signal, forming difference vectors;

calculating energy of said filtered difference vectors, forming an error signal;

choosing an excitation code, I, using the error signals, which best represents the received speech data;

calculating optimal excitation gain and optimal long term predictor gain for the chosen excitation codebook vector;

forming a synthetic excitation signal using said chosen excitation code, the optimal excitation gain and said optimal long term predictor gain;

calculating an energy of the speech data signal, forming a speech data energy value;

calculating an energy of the synthetic excitation signal, forming a synthetic excitation energy value;

determining a gain bias factor to more closely match the speech data energy value and the synthetic excitation energy value; and

quantizing the optimal excitation gain and the optimal long term predictor gain to minimize the error between the speech data signal and the synthetic excitation signal.

6. A speech coder for providing a codevector and associated gain terms in response to an input speech vector, the speech coder comprising:

a codebook search controller for choosing a codevector to represent the input speech vector;

a mean square error (MSE) modifier comprising;

an optimizer for optimizing a long term predictor coefficient and a gain term for the codevector, thereby forming an optimized long term predictor and an optimized gain term;

a bias generator for determining a gain bias factor to more closely match an energy of the code vector to the input speech vector; and

an alterer for altering the optimal long term predictor coefficient and the optimal gain term using the gain bias factor.

7. A method of matching energy of a reconstructed speech vector to an input speech vector comprising the steps of:

choosing at least one codevector to represent the input speech vector;

determining a gain term for each of the at least one codevector;

combining the chosen codevector, using the corresponding codevector gain term(s), to produce a combined excitation vector;

filtering the combined excitation vector to produce a reconstructed speech vector,

determining a gain bias factor to more closely match an energy of the reconstructed speech vector to an energy of the input speech vector; and

altering the gain term using the gain bias factor.

8. A method of matching energy of a reconstructed speech vector to an input speech vector comprising the steps of:

choosing at least one codevector to represent the input speech vector;

determining a long term predictor coefficient and a gain term for each of the at least one codevectors;

combining a long term predictor vector and the chosen codevector(s), using the long term predictor coefficient and the codevector gain term(s) to produce a combined excitation vector;

filtering the combined excitation vector to produce a reconstructed speech vector;

determining a gain bias factor to more closely match an energy of the reconstructed speech vector to an energy of the input speech vector; and

altering the long term predictor coefficient and the gain term using the gain bias factor.

9. The method of claim 8 where at least one of the at least one codevectors is the long term prediction vector.

10. The method of claim 8 wherein the step of determining a gain bias factor further comprises the steps of:

forming a synthetic excitation signal using the codevector, the optimal long term predictor and the optimal gain term;

calculating the energy of the input speech vector, forming a speech data energy value;

calculating the energy of the synthetic excitation signal, forming a synthetic excitation energy value;

calculating a ratio of the speech data energy value and the synthetic excitation energy value; and

calculating a square root of the ratio, forming the gain bias factor.

11. The method of claim 10 wherein the step of determining a gain bias factor further comprises the step of limiting the ratio between an upper bound and a lower bound.

12. The method of claim 10 wherein the step of altering further comprises:

adjusting the input speech vector by the gain bias factor, thereby forming an adjusted input speech vector; and

quantizing the optimal long term predictor coefficient and the optimal gain term to minimize the error between the adjusted input speech vector and the synthetic excitation signal.

13. A method of speech coding comprising the steps of:

receiving a speech data signal;

providing excitation vectors in response to said step of receiving;

determining an excitation gain coefficient and a long term predictor coefficient for use by a long term predictor filter and a Pth-order short term predictor filter;

filtering said excitation vectors utilizing said long term predictor filter and said short term predictor filter, forming filtered excitation vectors;

comparing said filtered excitation vectors to said speech data signal, forming difference vectors;

calculating energy of said difference vectors, forming an error signal;

choosing an excitation code, I, using the error signals, which best represents the received speech data;

calculating optimal excitation gain and optimal long term predictor gain for the chosen excitation codebook vector;

forming a synthetic excitation signal using said chosen excitation code, the optimal excitation gain and said optimal long term predictor gain;

filtering a synthetic excitation signal to form a synthetic speech signal,

calculating an energy of the speech data signal, forming a speech data energy value;

calculating an energy of the synthetic speech signal, forming a synthetic speech energy value;

determining a gain bias factor to more closely match the speech data energy value and the synthetic speech energy value;

adjusting speech data signal based on a gain bias factor; and

quantizing the excitation gain and the long term predictor gain to minimize the error between the adjusted speech data signal and the synthetic speech signal.