Spoken document summarization using acoustic, prosodic and semantic information

Chien Lin Huang, Chia Hsin Hsieh, Chung-Hsien Wu

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

5 Citations (Scopus)

Abstract

This paper presents a spoken document summarization scheme using acoustic, prosodic and semantic information. First, speech recognition confidence is estimated to choose reliable words from the speech transcription. Prosodic information, including pitch and energy, is used for stressed word selection. Latent semantic indexing (LSI) is adopted to identify significant words. Finally, word trigram and semantic dependency is measured to include the syntactic and semantic information for speech summarization. The dynamic programming (DP) algorithm is used to find the best summarization result according to the summarization score estimated from the above five measures. Finally, the summarized result is presented by the concatenation of the summarized speech words. Experimental results indicate that the proposed approach effectively extracts important words and gives a promising speech summary.

Original languageEnglish
Title of host publicationIEEE International Conference on Multimedia and Expo, ICME 2005
Pages434-437
Number of pages4
DOIs
Publication statusPublished - 2005 Dec 1
EventIEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands
Duration: 2005 Jul 62005 Jul 8

Publication series

NameIEEE International Conference on Multimedia and Expo, ICME 2005
Volume2005

Other

OtherIEEE International Conference on Multimedia and Expo, ICME 2005
CountryNetherlands
CityAmsterdam
Period05-07-0605-07-08

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'Spoken document summarization using acoustic, prosodic and semantic information'. Together they form a unique fingerprint.

Cite this