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

Chung Hsien Wu, Yeou Jiunn Chen, Yu Chun Hung

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

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 keyword. 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.

Original languageEnglish
Publication statusPublished - 1998
Event5th International Conference on Spoken Language Processing, ICSLP 1998 - Sydney, Australia
Duration: 1998 Nov 301998 Dec 4

Conference

Conference5th International Conference on Spoken Language Processing, ICSLP 1998
Country/TerritoryAustralia
CitySydney
Period98-11-3098-12-04

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language

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