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Paper Abstract and Keywords
Presentation 2013-12-19 17:15
Speaker-dependent conditional restricted Boltzmann machine for voice conversion
Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we present a voice conversion (VC) method that utilizes conditional restricted Boltzmann machines (CRBMs) for each speaker to obtain time-invariant speaker-independent spaces where voice features are converted more easily than those in an original acoustic feature space. First, we train two CRBMs for a source and target speaker independently using speaker-dependent training data (without the need to parallelize the training data). Then, a small number of parallel data are fed into each CRBM and the high-order features produced by the CRBMs are used to train a concatenating neural network (NN) between the two CRBMs. Finally, the entire network (the two CRBMs and the NN) is fine-tuned using the acoustic parallel data. Through voice-conversion experiments, we confirmed the high performance of our method in terms of objective and subjective evaluations, comparing it with conventional GMM, NN, and speaker-dependent DBN approaches.
Keyword (in Japanese) (See Japanese page) 
(in English) Voice conversion / conditional restricted Boltzmann machine / deep learning / speaker specific features / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 366, SP2013-88, pp. 83-88, Dec. 2013.
Paper # SP2013-88 
Date of Issue 2013-12-12 (SP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee SP IPSJ-SLP  
Conference Date 2013-12-19 - 2013-12-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) 15th Symposium on Spoken Language 
Paper Information
Registration To SP 
Conference Code 2013-12-SP-SLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Speaker-dependent conditional restricted Boltzmann machine for voice conversion 
Sub Title (in English)  
Keyword(1) Voice conversion  
Keyword(2) conditional restricted Boltzmann machine  
Keyword(3) deep learning  
Keyword(4) speaker specific features  
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1st Author's Name Toru Nakashika  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Tetsuya Takiguchi  
2nd Author's Affiliation Kobe University (Kobe Univ.)
3rd Author's Name Yasuo Ariki  
3rd Author's Affiliation Kobe University (Kobe Univ.)
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Speaker
Date Time 2013-12-19 17:15:00 
Presentation Time 25 
Registration for SP 
Paper # IEICE-SP2013-88 
Volume (vol) IEICE-113 
Number (no) no.366 
Page pp.83-88 
#Pages IEICE-6 
Date of Issue IEICE-SP-2013-12-12 


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