Speech recognition of a named entity

Tatsuhiko Tomita*, Yoshiyuki Okimoto, Hirofumi Yamamoto, Yoshinori Sagisaka

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

A hierarchical language model is newly applied to identify a named entity consisting of multiple word sequences for continuous speech recognition. By redesigning an out-of-vocabulary model of a single word using phonotactic constraints for a named entity, a hierarchical model is composed harmoniously with conventional word and word-class N-grams. Continuous speech recognition experiments aiming at movie-title identification showed the effectiveness of this modeling in the task of inquiries on these titles. These results ensure that the proposed hierarchical language modeling architecture is applicable to multiple word successions for speech recognition to cope with unregistered expressions and enables the mix use of different statistics harmoniously.

Original languageEnglish
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesI1057-I1060
ISBN (Print)0780388747, 9780780388741
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: 2005 Mar 182005 Mar 23

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeI
ISSN (Print)1520-6149

Conference

Conference2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period05/3/1805/3/23

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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