Method for estimating fractional base sound of code excitation linear predicted speech encoder

Abstract

The invention relates to a method for estimating fractional pitch of a code-excited linear prediction voice coder, which directly estimates a peak value position through a polynomial interpolation and obtains the fractional pitch estimation. A fractional pitch estimation value is obtained by the following steps: (1) performing an open-loop pitch estimation on an object signal, calculating an estimation value Top of an open-loop integer pitch; (2) continuing to perform the open-loop pitch estimation and calculating a close-loop correlation sequence C(k) in a given neighborhood of the open-loop integer pitch estimation value Top; (3) if a peak value point Tcl of the close-loop correlation sequence C(k) appears at two ends of the given neighborhood, then the fractional pitch estimation value Tfr being zero; if the peak point Tcl appears in the given neighborhood, then performing a polynomial fitting based on the peak point value Tcl and the values of the former point Tcl-1 and the post point Tcl+1, solving out the peak value position Tr, performing linear quantization to the peak value position Tr according to an interpolation factor D and obtaining the fractional pitch estimation value Tfr, a linear quantization formula being Tfr=round(Tr*D). Under the premise that the accurate fractional pitch estimation value is obtained and the prediction grain is improved, the invention effectively reduces the computational complexity and system overhead.

Description

technical field [0001] The invention belongs to the field of voice communication, in particular to a fractional pitch estimation method for a code-excited linear prediction speech coder. Background technique [0002] Code Excited Linear Prediction (Code Excited Linear Prediction, CELP) comprehensively utilizes the short-term prediction characteristics, long-term prediction characteristics and vector quantization method of speech to obtain coding gain, and has been widely used in low-bit-rate speech communication. Pitch period estimation is one of the key factors affecting prediction gain in long-term prediction. In the digitization process of the speech signal, since the pitch period of the speech signal is usually not an integer multiple of the sampling interval T, if the integer pitch prediction is directly used, the pitch period obtained in the discrete domain will be -0.5T~ 0.5T mismatch. If fractional pitch estimation is used, the gain reduction caused by this mismatc...

AI Technical Summary

Problems solved by technology

However, the existing fractional pitch estimation method has the following defects: the fractional pitch estimation value required for the long-term prediction of the first-order fraction only represents the position of the peak value of the interpolation sequence, rather than the peak value; on the other hand, the interpolation composed of upsampling and low-pass filtering Filter cannot accommodate variable interpolation factors

Therefore, in the prior art, the realization of fractional pitch estimation requires interpolation and comparison operations, the algorithm is complex and the memory overhead is large, and the efficiency of obtaining the fractional pitch estimation value is low.

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