Incorporating AM-FM effect in voiced speech for probabilistic acoustic tube model

Yang Zhang, Zhijian Ou, Mark Hasegawa-Johnson

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

Abstract

A complete speech model can improve performance for many speech applications. Probabilistic Acoustic Tube (PAT) is a probabilistic generative model of speech that has been shown potentially useful in a number of speech processing tasks. A point missing in previous PAT models is that they overlook AM/FM effect in voiced speech, which is in fact common and non-negligible. In this paper, we significantly improve the voiced modeling of PAT with a probabilistic model of AM/FM effect, which is developed from Bayesian Spectrum Estimation method. Experiments show that the new PAT is able to fit the voiced speech spectrum with greater accuracy in the presence of AM/FM effect.

Original languageEnglish (US)
Title of host publication2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479974504
DOIs
StatePublished - Nov 24 2015
EventIEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2015 - New Paltz, United States
Duration: Oct 18 2015Oct 21 2015

Publication series

Name2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2015

Other

OtherIEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2015
Country/TerritoryUnited States
CityNew Paltz
Period10/18/1510/21/15

Keywords

  • AM/FM
  • Speech modeling
  • generative model
  • speech analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing
  • Media Technology

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