A hidden Markov model based visual speech synthesizer

Jay J. Williams, Aggelos K. Katsaggelos, Mark A. Randolph

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

7 Scopus citations

Abstract

This paper describes a hidden Markov model (HMM) based visual synthesizer designed to assist persons with impairedhearing. This synthesizer builds on results in the area of audio-visual speech recognition. We describe how a correlation HMM can be used to integrate independent acoustic and visual HMMs for speech-to-visual synthesis. Our results show that an HMM correlating model can significantly improve synchronization errors versus techniques which compensate for rate differences through scaling.

Original languageEnglish (US)
Title of host publicationImage and Multidimensional Signal ProcessingMultimedia Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2393-2396
Number of pages4
ISBN (Electronic)0780362934
DOIs
StatePublished - Jan 1 2000
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: Jun 5 2000Jun 9 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
ISSN (Print)1520-6149

Other

Other25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
CountryTurkey
CityIstanbul
Period6/5/006/9/00

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A hidden Markov model based visual speech synthesizer'. Together they form a unique fingerprint.

Cite this