Open Access

Perceptual Continuity and Naturalness of Expressive Strength in Singing Voices Based on Speech Morphing

  • Tomoko Yonezawa1, 2, 3Email author,
  • Noriko Suzuki4,
  • Shinji Abe1, 3,
  • Kenji Mase2, 1 and
  • Kiyoshi Kogure5
EURASIP Journal on Audio, Speech, and Music Processing20072007:023807

DOI: 10.1155/2007/23807

Received: 30 November 2006

Accepted: 17 August 2007

Published: 1 October 2007

Abstract

This paper experimentally shows the importance of perceptual continuity of the expressive strength in vocal timbre for natural change in vocal expression. In order to synthesize various and continuous expressive strengths with vocal timbre, we investigated gradually changing expressions by applying the STRAIGHT speech morphing algorithm to singing voices. Here, a singing voice without expression is used as the base of morphing, and singing voices with three different expressions are used as the target. Through statistical analyses of perceptual evaluations, we confirmed that the proposed morphing algorithm provides perceptual continuity of vocal timbre. Our results showed the following: (i) gradual strengths in absolute evaluations, and (ii) a perceptually linear strength provided by the calculation of corrected intervals of the morph ratio by the inverse (reciprocal) function of an equation that approximates the perceptual strength. Finally, we concluded that applying continuity was highly effective for achieving perceptual naturalness, judging from the results showing that (iii) our gradual transformation method can perform well for perceived naturalness.

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Authors’ Affiliations

(1)
ATR Intelligent Robotics and Communication Laboratories
(2)
Nagoya University
(3)
ATR Media Information Science Laboratories
(4)
National Institute of Information and Communication Technology/ATR Cognitive Information Science Laboratories
(5)
ATR Knowledge Science Laboratories

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Copyright

© Tomoko Yonezawa et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.