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Patent

Technique for modifying reference vector quantized speech feature signals

Abstract
A signal processing arrangement uses a codebook of first vector quantized speech feature signals formed responsive to a large collection of speech feature signals. The codebook is altered by combining the first speech feature signals of the codebook with second speech feature signals generated responsive to later input speech patterns during normal speech processing. A speaker recognition template can be updated in this fashion to take account of change which may occur in the voice and speaking characteristics of a known speaker.

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Citations
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References
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Journal Article

Vector quantization

TL;DR: During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes.
Journal ArticleDOI

Vector quantization in speech coding

TL;DR: This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization, and focuses primarily on the coding of speech signals and parameters.
Journal ArticleDOI

Advances in Pattern Recognition

PatentDOI

Hidden Markov model speech recognition arrangement

TL;DR: In this paper, a speech recognizer includes a plurality of stored constrained hidden Markov model reference templates and a set of stored signals representative of prescribed acoustic features of the said plurality of reference patterns.
Journal ArticleDOI

Vector quantization: A pattern-matching technique for speech coding

TL;DR: Recent results obtained in waveform coding of speech with vector quantization are reviewed, with Vector quantization appearing to be a suitable coding technique which caters to this dual requirement of effective speech coding.