Linear prediction coefficient analyzing apparatus for the auto-correlation function of a digital speech signal
First Claim
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.
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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.
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Citations
4 Claims
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1. A linear prediction coefficient analyzing apparatus, comprising:
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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. - View Dependent Claims (2, 3, 4)
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Specification