Perceptual similarity measurement of speech by combination of acoustic features

Yoshihiro Adachi*, Shinichi Kawamoto, Shigeo Morishima, Satoshi Nakamura

*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

Future cast system is a new entertainment system where participant's face is captured and rendered into the movie as an instant Computer Graphics (CG) movie star, which had been first exhibited at the 2005 World Exposition in Aichi Japan. We are working to add new functionality which enables mapping not only faces but also speech individualities to the cast. Our approach is to find a speaker with the closest speech individuality and apply voice conversion. This paper investigates acoustic features to estimate perceptual similarity of speech individuality. We propose a method linearly combined eight acoustic features related to the perception of speech individualities. The proposed method optimizes weights for the acoustic features considering perceptual similarities. We have evaluated performance of our method with Spearman's rank correlation coefficients to perceptual similarities. As the results, the experiments evidenced that the proposed method achieves a correlation coefficient of 0.66.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages4861-4864
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 2008 Mar 312008 Apr 4

Publication series

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

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period08/3/3108/4/4

Keywords

  • Acoustic correlators
  • Speaker recognition
  • Speech analysis

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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