Syllable-based Chinese text/spoken document retrieval using text/speech queries

Bo Ren Bai, Berlin Chen, Hsin Min Wang

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


In light of the rapid growth of Chinese information resources on the Internet, this study investigates a novel approach that deals with the problem of Chinese text and spoken document retrieval using both text and speech queries. By properly utilizing the monosyllabic structure of the Chinese language, the proposed approach estimates the statistical similarity between the text/speech queries and the text/spoken documents at the phonetic level using the syllable-based statistical information. The investigation successfully implemented a prototype system with an interface supporting some user-friendly functions and the initial test results demonstrate the feasibility of the proposed approach.

Original languageEnglish
Pages (from-to)603-616
Number of pages14
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number5
Publication statusPublished - 2000 Aug
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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