Discriminating capabilities of syllable-based features and approaches of utilizing them for voice retrieval of speech information in Mandarin Chinese

Berlin Chen, Hsin Min Wang, Lin Shan Lee

Research output: Contribution to journalArticle

50 Citations (Scopus)

Abstract

With the rapidly growing use of the audio and multimedia information over the Internet, the technology for retrieving speech information using voice queries is becoming more and more important. In this paper, considering the monosyllabic structure of the Chinese language, a whole class of syllable-based indexing features, including overlapping segments of syllables and Syllable pairs separated by a few syllables, is extensively investigated based on a Mandarin broadcast news database. The strong discriminating capabilities of such syllable-based features were verified by comparing with the word- or character-based features. Good approaches for better utilizing such capabilities, including fusion with the word- and character-level information and improved approaches to obtain better syllable-based features and query expressions, were extensively investigated. Very encouraging experimental results were obtained.

Original languageEnglish
Pages (from-to)303-314
Number of pages12
JournalIEEE Transactions on Speech and Audio Processing
Volume10
Issue number5
DOIs
Publication statusPublished - 2002 Jul 1

Keywords

  • Confidence measure
  • Retrieval of speech information
  • Syllable-based features
  • Term association matrix

ASJC Scopus subject areas

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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