Word Spotting in Conversational Speech Based on Phonemic Unit Likelihood by Mutual Information Criterion

Shigeki Okawa, Tetsunori Kobayashi, Katsuhiko Shirai

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

This paper proposes a novel scheme for keyword-spotting in conversational speech using frame-level likelihood of phonemes and statistics of their duration. Since spontaneous utterances include many ill-formed sentences, it is most difficult to realize a highly advanced continuous speech recognition system based on a top-down syntax driven process. We, therefore, propose a bottom-up method to detect keywords in continuous speech based on a dynamical programming technique using both phonemic and durational likelihood. Our algorithm basically depends on island-driven both-side-free DP method. In the performance test of the speaker-dependent keyword spotting, it was found that, compared to the conventional continuous DP method, the erroneous candidates and the processing time decreases to 1/6 in new method. This result shows the feasibility of our method for continuous speech recognition, especially for conversational style utterances.

Original languageEnglish
Pages1281-1284
Number of pages4
Publication statusPublished - 1993
Event3rd European Conference on Speech Communication and Technology, EUROSPEECH 1993 - Berlin, Germany
Duration: 1993 Sep 221993 Sep 25

Conference

Conference3rd European Conference on Speech Communication and Technology, EUROSPEECH 1993
Country/TerritoryGermany
CityBerlin
Period93/9/2293/9/25

ASJC Scopus subject areas

  • Software
  • Linguistics and Language
  • Computer Science Applications
  • Communication

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