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Volumn 08-12-September-2016, Issue , 2016, Pages 1647-1651

A voice conversion mapping function based on a stacked joint-autoencoder

Author keywords

Autoencoder; Deep neural network; Joint autoencoder; Voice conversion

Indexed keywords

FUNCTION EVALUATION; LEARNING SYSTEMS; MAPPING; QUALITY CONTROL; SPEECH COMMUNICATION;

EID: 84994219829     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: 10.21437/Interspeech.2016-1437     Document Type: Conference Paper
Times cited : (9)

References (18)
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    • Semi-supervised training of a voice conversion mapping function using a joint-autoencoder
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    • Hamidreza Mohammadi, S.1    Kain, A.2
  • 8
    • 84946027999 scopus 로고    scopus 로고
    • Voice conversion using deep bidirectional long short-term memory based recurrent neural networks
    • Lifa Sun, Shiyin Kang, Kun Li, and Helen Meng. Voice conversion using deep bidirectional long short-term memory based recurrent neural networks. In Proceedings of the ICASSP, 2015.
    • (2015) Proceedings of the ICASSP
    • Sun, L.1    Kang, S.2    Li, K.3    Meng, H.4
  • 9
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    • Alleviating the one-to-many mapping problem in voice conversion with context-dependent modelling
    • Elizabeth Godoy, Olivier Rosec, and Thierry Chonavel. Alleviating the one-to-many mapping problem in voice conversion with context-dependent modelling. In Proceeding of the INTERSPEECH, 2009.
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    • Godoy, E.1    Rosec, O.2    Chonavel, T.3
  • 11
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    • Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory
    • Tomoki Toda, Alan W Black, and Keiichi Tokuda. Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory. IEEE Transactions on Audio, Speech, and Language Processing, 15(8):2222-2235, 2007.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.