Presentation 2004/12/14
NAM-toSpeech Conversion Based on Gaussian Mixture Model
Tomoki TODA, Kiyohiro SHIKANO,
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Abstract(in English) In order to realize man-to-man communication using Non-Audible Murmur (NAM), which can not be heard by people around a speaker, we perform conversion from NAM to speech (NAM-to-Speech). NAM-to-Speech is a potential technique for realizing "non-speech telephone" that is a technique for communicating each other by talking in NAM and hearing in speech. In this paper, we apply a statistical conversion method based on Gaussian Mixture Model (GMM) to NAM-to-Speech. In advance, we train GMMs for representing correlations between acoustic features of NAM and speech. In the conversion, we estimate acoustic spectral and FQ features of speech based on maximum likelihood criterion and synthesize the converted speech with the vocoder. From results of preliminary subjective evaluations on intelligibility and naturalness, it is shown that the NAM-to-Speech with GMMs can convert NAM to more natural voice while keeping intelligibility.
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Keyword(in English) NAM / NAM-to-Speech / GMM / intelligibility / naturalness
Paper # NLC2004-67,SP2004-107
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Committee NLC
Conference Date 2004/12/14(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) NAM-toSpeech Conversion Based on Gaussian Mixture Model
Sub Title (in English)
Keyword(1) NAM
Keyword(2) NAM-to-Speech
Keyword(3) GMM
Keyword(4) intelligibility
Keyword(5) naturalness
1st Author's Name Tomoki TODA
1st Author's Affiliation Graduate School of Engineering, Nagoya Institute of Technology()
2nd Author's Name Kiyohiro SHIKANO
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2004/12/14
Paper # NLC2004-67,SP2004-107
Volume (vol) vol.104
Number (no) 539
Page pp.pp.-
#Pages 6
Date of Issue