Mixture of factor analyzers using priors from non-parallel speech for voice conversion

A robust voice conversion function relies on a large amount of parallel training data, which is difficult to collect in practice. To tackle the sparse parallel training data problem in voice conversion, this paper describes a mixture of factor analyzers method which integrates prior knowledge from n...

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Bibliographic Details
Main Authors: Wu, Zhizheng, Kinnunen, Tomi, Chng, Eng Siong, Li, Haizhou
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/102726
http://hdl.handle.net/10220/16436
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Institution: Nanyang Technological University
Language: English