A technique for estimating intensity of emotional expressions and speaking styles in speech based on multiple-regression HSMM

Takashi Nose, Takao Kobayashi

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In this paper, we propose a technique for estimating the degree or intensity of emotional expressions and speaking styles appearing in speech. The key idea is based on a style control technique for speech synthesis using a multiple regression hidden semi-Markov model (MRHSMM), and the proposed technique can be viewed as the inverse of the style control. In the proposed technique, the acoustic features of spectrum, power, fundamental frequency, and duration are simultaneously modeled using the MRHSMM. We derive an algorithm for estimating explanatory variables of the MRHSMM, each of which represents the degree or intensity of emotional expressions and speaking styles appearing in acoustic features of speech, based on a maximum likelihood criterion. We show experimental results to demonstrate the ability of the proposed technique using two types of speech data, simulated emotional speech and spontaneous speech with different speaking styles. It is found that the estimated values have correlation with human perception.

Original languageEnglish
Pages (from-to)116-124
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE93-D
Issue number1
DOIs
Publication statusPublished - 2010
Externally publishedYes

Keywords

  • Emotion recognition
  • Emotional expression
  • Hidden semi-Markov model (HSMM)
  • Intensity of style
  • Multiple-regression HSMM (MRHSMM)
  • Speaking style

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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