Fast search algorithm for VQ-based recognition of isolated words

Sin-Horng Chen*, J. S. Pan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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.

Original languageEnglish
Pages (from-to)391-396
Number of pages6
JournalIEE Proceedings, Part I: Communications, Speech and Vision
Volume136 pt 1
Issue number6
StatePublished - 1 Dec 1989

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