Method for vector quantizing speech signals

• US 6,175,817 B1
• Filed: 05/18/1998
• Issued: 01/16/2001
• Est. Priority Date: 11/20/1995
• Status: Expired due to Term

• Current Assignee: IPCom GmbH & Co KG
• Original Assignee: Robert Bosch GmbH
• Inventors: Waechter, Bertram, Mueller, Joerg-Martin
• Primary Examiner(s): Zele, Krista
• Assistant Examiner(s): Opsasnick, Michael N.
• Application Number:
  US09/080,778
• Time in Patent Office: 974 Days
• Field of Search: 704/219, 704/222
• 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

Abstract

Two codebooks each consisting of a filter memory are used for vector quantizing of a speech sample. Fixed excitation vectors and pitch parameters of a prediction filter are entered in the respective codebooks, which are actualized in time intervals. To improve the speech quality, respectively two vectors from the adaptive codebook which are best in respect to an error criterion are linked with all vectors of the fixed codebook. The value which best matches an original speech scanned value is selected from the linkages. The entries in the first codebook are advantageously thinned out by suppressing vector components taken from sum bits of two frame sections into which the speech sample is divided until the processing work is no more than the processing work with only one selected best vector from the second codebook.

Claims

1. A method for vector quantizing a speech sample, said method comprising the following steps:

a) entering fixed excitation vectors of an LPC filter for speech prediction in a first codebook (CB1),

b) entering excitation vectors of a pitch synthesis filter in a second codebook (CB2);

c) modifying said excitation vectors in said second codebook (CB2) after each sub-frame;

d) establishing a predetermined error criterion for selection of excitation vectors from the second codebook (CB2);

e) selecting at least two of said excitation vectors from the second codebook (CB2) to obtain optimum prediction values according to said predetermined error criterion;

f) linking said at least two excitation vectors selected in step e) with a plurality of said excitation vectors from said first codebook (CB1) to form a set of linked vectors;

g) selecting a matching vector from said linked vectors having a minimal variation from said speech sample according to a predetermined variation guideline; and

h) thinning out said fixed excitation vectors in said first codebook.

2. The method as defined in claim 1, further comprising determining an error of each of said linked vectors from said first codebook (CB1) in relation to the speech sample so as to take into consideration at least two pitch predictors selected from the second codebook (CB2).

3. The method as defined in claim 1, wherein said thinning out of the first codebook (CB1) occurs by suppressing vector components taken from sum bits of two frame sections into which said speech sample is divided.

4. The method as defined in claim 1, wherein said thinning out of the first codebook (CB1) occurs until processing efforts are no more than processing efforts would be with only one selected best one of said excitation vectors from the second codebook (CB2).

5. The method as defined in claim 1, wherein said predetermined variation guideline consists of said predetermined error criterion.

6. A method for vector quantizing a speech sample, said method comprising the following steps:

a) entering fixed excitation vectors of an LPC filter for speech prediction in a first codebook (CB1) comprising a first filter memory,

b) entering excitation vectors of a pitch synthesis filter in a second codebook (CB2) comprising a second filter memory;

c) modifying said excitation vectors in said second codebook (CB2) after each sub-frame;

d) establishing a predetermined error criterion for selection of excitation vectors from the second codebook (CB2);

e) selecting at least two of said excitation vectors from the second codebook (CB2) to obtain optimum prediction values according to said predetermined error criterion;

f) linking said at least two excitation vectors selected in step e) with a plurality of said excitation vectors from said first codebook (CB1) to form a set of linked vectors;

g) selecting a matching vector from said linked vectors having a minimal variation from said speech sample according to a predetermined variation guideline; and

h) thinning out said fixed excitation vectors in said first codebook, wherein said thinning out occurs by suppressing vector components taken from sum bits of two frame sections into which said speech sample is divided.