NDLI: Statistical Voice Conversion Based on Noisy Channel Model

Content Provider	IEEE Xplore Digital Library
Author	Saito, D. Watanabe, S. Nakamura, A. Minematsu, N.
Copyright Year	2006
Abstract	This paper describes a novel framework of voice conversion effectively using both a joint density model and a speaker model. In voice conversion studies, approaches based on the Gaussian mixture model (GMM) with probabilistic densities of joint vectors of a source and a target speakers are widely used to estimate a transform function between both the speakers. However, to achieve sufficient quality, these approaches require a parallel corpus which contains plenty of utterances with the same linguistic content spoken by both the speakers. In addition, the joint density GMM methods often suffer from overtraining effects when the amount of training data is small. To compensate for these problems, we propose a voice conversion framework, which integrates the speaker GMM of the target with the joint density model using a noisy channel model. The proposed method trains the joint density model with a few parallel utterances, and the speaker model with nonparallel data of the target, independently. It can ease the burden on the source speaker. Experiments demonstrate the effectiveness of the proposed method, especially when the amount of the parallel corpus is small.
Sponsorship	IEEE Signal Processing Society
Starting Page	1784
Ending Page	1794
Page Count	11
File Size	684222
File Format	PDF
ISSN	15587916
Volume Number	20
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Joints Vectors Speech Noise measurement Channel models Pragmatics Speech enhancement voice conversion (VC) Joint density model noisy channel model probabilistic integration speaker model
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering

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