Emotional speech recognition based on style estimation and adaptation with multiple-regression HMM

Yusuke Ijima, Makoto Tachibana, Takashi Nose, Takao Kobayashi

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

9 Citations (Scopus)

Abstract

This paper proposes a technique for emotional speech recognition which enables us to extract paralinguistic information as well as linguistic information contained in speech signal. The technique is based on style estimation and style adaptation using multiple-regression HMM. Recognition process consists of two stages. In the first stage, a style vector that represents the emotional expression category and intensity of its variation of input speech is estimated on a sentence-by-sentence basis. Then the acoustic models are adapted using the estimated style vector and standard HMM-based speech recognition is performed in the second stage. We assess the performance of the proposed technique on the recognition of acted emotional speech uttered by both professional narrators and non-professional speakers and show the effectiveness of the technique.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages4157-4160
Number of pages4
DOIs
Publication statusPublished - 2009 Sep 23
Externally publishedYes
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: 2009 Apr 192009 Apr 24

Publication series

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

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
CountryTaiwan, Province of China
CityTaipei
Period09/4/1909/4/24

Keywords

  • Multiple-regression HMM (MRHMM)
  • Speaker adaptation
  • Style adaptation
  • Style estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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