NDLI: Voice conversion based on joint pitch and spectral transformation with component group-GMM

Content Provider	IEEE Xplore Digital Library
Author	Jianchun Ma Wenju Liu
Copyright Year	2005
Description	Author affiliation: Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China (Jianchun Ma; Wenju Liu)
Abstract	Spectral and pitch are two most important features in voice conversion which including a majority of speaker identity information. Some researchers use the GMM (Gaussian mixture model) to model the joint spectral and pitch. But these two features have the discrepancy of unit and meaning, so should do some processing before training the model. In this paper, a new framework CG-GMM (component-group GMM) is used for the joint pitch and spectral transformation. Experiments are setup and compared with the previous approach of voice conversion. The converted speeches indicate satisfactory speech quality and speaker identifiability. Meanwhile the speaking style is much like to the target speaker.
Starting Page	199
Ending Page	203
File Size	1401083
Page Count	5
File Format	PDF
ISBN	0780393619
DOI	10.1109/NLPKE.2005.1598734
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood estimation Discrete transforms Speech analysis Laboratories Natural languages Artificial neural networks Spatial databases Pattern recognition Speech synthesis Data mining
Content Type	Text
Resource Type	Article

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