Linear prediction coefficient analyzing apparatus for the auto-correlation function of a digital speech signal

• US 6,167,373 A
• Filed: 12/30/1999
• Issued: 12/26/2000
• Est. Priority Date: 12/19/1994
• Status: Expired due to Term

• Current Assignee: Panasonic Intellectual Property Corporation of America (Panasonic Holdings Corporation)
• Original Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Inventors: Morii, Toshiyuki
• Primary Examiner(s): Hudspeth, David R.
• Assistant Examiner(s): Chawan, Vijay B
• Application Number:
  US09/475,248
• Time in Patent Office: 362 Days
• Field of Search: 704/219, 704/216, 704/217, 704/218, 704/262
• US Class Current: 704/219
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 15/16 using artificial neural networks
• CPC Class Codes: G10L 19/06 Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients
• CPC Class Codes: G10L 19/09 Long term prediction, i.e. removing periodical redundancies, e.g. by using adaptive codebook or pitch predictor
• CPC Class Codes: G10L 19/18 Vocoders using multiple modes
• CPC Class Codes: G10L 2021/02168 the estimation exclusively taking place during speech pauses
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 21/0216 characterised by the method used for estimating noise
• CPC Class Codes: G10L 25/06 the extracted parameters being correlation coefficients
• CPC Class Codes: G10L 25/12 the extracted parameters being prediction coefficients
• CPC Class Codes: G10L 25/27 characterised by the analysis technique

Abstract

A sample speech is analyzed by a speech analyzing unit to obtain sample characteristic parameters, and a coding distortion is calculated from the sample characteristic parameters in each of a plurality of coding modules. The sample characteristic parameters and the coding distortions are statistically processed by a statistical processing unit to obtain a coding module selecting rule. Thereafter, when a speech is analyzed by the speech analyzing unit to obtain characteristic parameters, an appropriate coding module is selected by a coding module selecting unit from the coding modules according to the coding module selecting rule on condition that a coding distortion for the characteristic parameters is minimized in the appropriate coding module. Thereafter, the characteristic parameters of the speech are coded in the appropriate coding module, and a coded speech is obtained. When the coded speech is decoded, a reproduced speech is obtained. Accordingly, because an appropriate coding module can be easily selected from a plurality of coding modules according to the coding module selecting rule, any allophone occurring in a reproduced speech can be prevented at a low calculation volume.

Claims

1. A linear prediction coefficient analyzing apparatus, comprising:

input speech receiving means providing an input digital signal indicative of an input speech;

extracting means responsive to said input digital signal fed from said input speech receiving means for extracting a plurality of partial analyzing periods from an analyzing period for said input digital signal and extracting a plurality of partial digital signals at the partial analyzing periods from said input digital signal;

window coefficient multiplying means for multiplying each of the partial digital signals extracted by the extracting means by a window coefficient to generate a window-processed partial digital signal for each of the partial analyzing periods extracted by the extracting means;

auto-correlation analyzing means for analyzing an auto-correlation of each of the window processed partial digital signals generated by the window coefficient multiplying means to generate an auto-correlation function for each of the partial analyzing periods;

auto-correlation function synthesizing means for weighting each of the auto correlation functions generated by the auto correlation analyzing means with a weighting factor to generate a weighted auto-correlation function for each of the partial analyzing periods and adding the weighted auto-correlation functions to each other to generate a synthesized auto-correlation function; and

linear prediction coefficient analyzing means for performing a linear prediction analysis for the synthesized auto-correlation function generated by the auto-correlation function synthesizing means to obtain a liner prediction coefficient for the digital signal.

2. An apparatus according to claim 1 in which a sum of products obtained by multiplying one weighting factor used by the auto-corelation function synthesizing means and one window coefficient used by the window coefficient multiplying means for each of the partial analyzing periods is set to one.

3. An apparatus according to claim 1 in which the partial analyzing periods extracted by the extracting means are overlapping with each other.

4. An apparatus according to claim 1 in which the input digital signal is indicative of a digital input speech signal obtained from a piece of speech.