Content-based language models for spoken document retrieval

Hsin Min Wang, Berlin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Spoken document retrieval (SDR) has been extensively studied in recent years because of its potential use in navigating large multimedia collections in the near future. This paper presents a novel concept of applying the content-based language models to spoken document retrieval. In an example task for retrieval of Mandarin broadcast news, the content-based language models either trained with the automatic transcriptions of the spoken documents or adapted from the baseline language models using the automatic transcriptions of the spoken documents were used to create the more accurate recognition results and indexing terms from both the spoken documents and the speech queries. We report on some interesting findings obtained in this research.

Original languageEnglish
Title of host publicationProceedings of the 5th international Workshop on Information Retrieval with Asian Languages, IRAL 2000
PublisherAssociation for Computing Machinery, Inc
Pages149-155
Number of pages7
ISBN (Electronic)1581133006, 9781581133004
DOIs
Publication statusPublished - 2000 Nov 1
Event5th International Workshop on Information Retrieval with Asian Languages, IRAL 2000 - Hong Kong, China
Duration: 2000 Sep 302000 Oct 1

Publication series

NameProceedings of the 5th international Workshop on Information Retrieval with Asian Languages, IRAL 2000

Other

Other5th International Workshop on Information Retrieval with Asian Languages, IRAL 2000
CountryChina
CityHong Kong
Period00/9/3000/10/1

Keywords

  • Content-based language models
  • Speech recognition
  • Spoken document retrieval (SDR)

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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