5th International Conference on Spoken Language Processing

Sydney, Australia
November 30 - December 4, 1998

Telephone Speech Multi-Keyword Spotting Using Fuzzy Search Algorithm and Prosodic Verification

Chung-Hsien Wu, Yeou-Jiunn Chen, Yu-Chun Hung

National Cheng Kung University, China

In this paper a fuzzy search algorithm is proposed to deal with the recognition error for telephone speech. Since the prosodic information is a very special and important feature for Mandarin speech, we integrate the prosodic information into keyword verification. For multi-keyword detection, we define a keyword relation and a weighting function for reasonable keyword combinations. In the keyword recognizer, 94 INITIAL and 38 FINAL context-dependent Hidden Markov Models (HMM's) are used to construct the phonetic recognizer. For prosodic verification, a total of 175 context-dependent HMM's and five anti-prosodic HMM's are used. In this system, 1275 faculty names and department names are selected as the keywords. Using a test set of 3595 conversional speech utterance from 37 speakers (21 male, 16 female), the proposed fuzzy search algorithm and prosodic verification can reduce the error rate from 17.64% to 11.29% for multiple keywords embedded in non-keyword speech.

Full Paper

Bibliographic reference.  Wu, Chung-Hsien / Chen, Yeou-Jiunn / Hung, Yu-Chun (1998): "Telephone speech multi-keyword spotting using fuzzy search algorithm and prosodic verification", In ICSLP-1998, paper 0218.