A fast algorithm for large vocabulary keyword spotting application

Author

Huang, Eng-Fong ; Wang, Hsiao-Chum ; Soong, Frank K.

Author_Institution

Telecommun. Lab., Minist. of Commun., Chung-Li, Taiwan

Volume

2

Issue

3

fYear

1994

fDate

7/1/1994 12:00:00 AM

Firstpage

449

Lastpage

452

Abstract

Presents a fast algorithm for spotting a large number of keywords in unconstrained, continuous speech using an HMM-based continuous speech recognizer. This fast algorithm is based on a two stage scheme. In the first stage, the forward backward search is performed for detecting N most likely common subwords. In the second stage, the tree-trellis search is carried out to determine the optimum keyword by traversing the tree-structural vocabulary in an effective way. Compared with the conventional whole-word based keyword spotting algorithm, the proposed fast algorithm can drastically reduce the computational cost

Keywords

filtering and prediction theory; hidden Markov models; speech recognition; trees (mathematics); HMM; computational cost reduction; continuous speech recognizer; fast algorithm; ffilter models; forward backward search; large vocabulary keyword spotting; tree-structural vocabulary; tree-trellis search; unconstrained continuous speech; Computational efficiency; Health information management; Hidden Markov models; Speech recognition; Viterbi algorithm; Vocabulary;

fLanguage

English

Journal_Title

Speech and Audio Processing, IEEE Transactions on

Publisher

ieee

ISSN

1063-6676

Type

jour

DOI

10.1109/89.294361

Filename

294361