Fast search algorithm for VQ-based recognition of isolated words | Zendy

SsuHan Chen | Zendy; JengShyang Pan | Zendy

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Fast search algorithm for VQ-based recognition of isolated words

Author(s) -

SsuHan Chen,

JengShyang Pan

Publication year - 1989

Publication title -

iee proceedings i communications speech and vision

Language(s) - English

Resource type - Journals

eISSN - 2053-9053

pISSN - 0956-3776

DOI - 10.1049/ip-i-2.1989.0059

Subject(s) - codebook , feature vector , pattern recognition (psychology) , feature (linguistics) , search algorithm , algorithm , computational complexity theory , computer science , computation , matching (statistics) , reduction (mathematics) , distortion (music) , artificial intelligence , vector quantization , mathematics , amplifier , computer network , linguistics , philosophy , statistics , geometry , bandwidth (computing)

This paper presents a fast search algorithm for vector quantisation (VQ)-based recognition of isolated words. It incorporates the property of high correlation between speech feature vectors of consecutive frames with the method of triangular inequality elimination to relieve the computational burden of vector-quantising the test feature vectors by full code-book search, and uses the extended partial distortion method to compress the incomplete matching computations of widly mismatched words. Overall computational load can therefore be drastically reduced while the recognition performance of full search can be retained. Experimental results show that about 93% of multiplications and additions can be saved with a little increase of both comparisons and memory space.

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