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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Main Authors: | Wu, Zhizheng, Kinnunen, Tomi, Chng, Eng Siong, Li, Haizhou |
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Other Authors: | School of Computer Engineering |
Format: | Article |
Language: | English |
Published: |
2013
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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 |
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