Mandarin Chinese broadcast news retrieval and summarization using probabilistic generative models

Hsin Min Wang, Berlin Chen

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents our recent research work on applying probabilistic generative models to Mandarin Chinese broadcast news retrieval and summarization. Most models can be trained in either a supervised or unsupervised manner. In addition, both literal term matching and concept matching strategies have been intensively investigated. This paper also presents a prototype web-based Mandarin Chinese broadcast news retrieval system, which is based on technologies such as automatic story segmentation, automatic speech recognition, spoken document retrieval and summarization.

Original languageEnglish
Pages331-337
Number of pages7
Publication statusPublished - 2009 Dec 1
EventAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan
Duration: 2009 Oct 42009 Oct 7

Other

OtherAsia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009
CountryJapan
CitySapporo
Period09/10/409/10/7

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Communication

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