Speech coding system utilizing a recursive computation technique for improvement in processing speed

Abstract

This invention provides a novel speech coding system which recursively executes a filter-applied "Toeplitz characteristic" by causing a drive signal (i.e., an excitation signal) to be converted into a "Toeplitz matrix" when detecting a pitch period in which distortion of the input vector and the vector subsequent to the application of filter-applied computation to the drive signal vector in the pitch forecast called either "closed loop" or "compatible code book" is minimized. The vector quantization method substantially making up the speech coding system of the invention is characteristically used by the system.

Description

BACKGROUND OF THE INVENTION1. Field of the InventionThe present invention relates to a vector quantization system made available for compression and transmission of data of digital signals such as a speech signal for example. More particularly, the invention relates to a speech coding system using a vector quantization process for quantizing a vector by splitting the vector into data related to gain and index.2. Description of the Related ArtToday, the vector quantization system is one of the most important technologies attracting keen attention of those concerned, which is substantially a means for effectively encoding either a speech signal or an image signal by effectively compressing it. In particular, in the speech coding field, either the "code excited linear production (CELP)" system or the "vector excited coding (VXC)" system is known as the one to which the vector quantization system is applied. Further detail of the CELP system is described by M. R. Schroeder and B. S. Ata...

AI Technical Summary

Benefits of technology

The object of the invention is to provide a speech coding system which is capable of fully solving those problems mentioned above by minimizing t

Problems solved by technology

Nevertheless, any of these conventional systems has a particular problem in the performance of quantization.

If this occurs, since the overall error of the quantized vector is extremely large, any conventional vector quantization process cannot provide quantization of stable vectors at all.

Consequently, when the error grows itself beyond the negligible range after execution of subsequent quantization of the gain, overall error of the quantized vect

Images