Voice conversion in high-order eigen space using deep belief nets

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn , Issue , 2013, Pages 369-372

  Nakashika, Toru ^a   Takashima, Ryoichi ^a   Takiguchi, Tetsuya ^a   Ariki, Yasuo ^a  

^a KOBE UNIVERSITY   (Japan)

Author keywords

Deep belief nets; Deep learning; Voice conversion

Indexed keywords

ABSTRACTING; SPEECH COMMUNICATION;

DEEP ARCHITECTURES; DEEP BELIEF NETS; DEEP LEARNING; MODEL-BASED METHOD; NEURAL NETWORKS (NNS); OBJECTIVE CRITERIA; VOICE CONVERSION; VOICE CONVERSION TECHNIQUES;

SPEECH PROCESSING;

EID: 84906280857     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. A. Kain and M.W. Macon, "Spectral voice conversion for text-tospeech synthesis, " Proc. ICASSP, vol. 1, pp. 285-288, 1998.
2. C. Veaux and X. Robet, "Intonation conversion from neutral to expressive speech, " in Proc. INTERSPEECH, pp. 2765-2768, 2011.
3. K. Nakamura, T. Toda, H. Saruwatari, and K. Shikano, "Speakingaid systems using GMM- based voice conversion for electrolaryngeal speech, " Speech Communication, Vol. 54, No. 1, pp. 134- 146, 2012.
4. L. Deng, A. Acero, L. Jiang, J. Droppo, and X. Huang, "Highperformance robust speech recognition using stereo training data, " Proc. ICASSP, pp. 301-304, 2001.
5. A. Kunikoshi, Y. Qiao, N. Minematsu, and K. Hirose, "Speech generation from hand gestures based on space mapping, " Proc. INTERSPEECH, pp. 308-311, 2009.
6. M. Abe, S. Nakamura, K. Shikano, and H. Kuwabara, "Vice conversion through vector quantization, " in Proc. ICASSP, pp. 655- 658, 1988.
7. H. Valbret, E. Moulines and J. P. Tubach, "Voice transformation using PSOLA technique, " Speech Communication, Vol. 11, No. 2-3, pp. 175-187, 1992.
8. Y. Stylianou, O. Cappe, and E. Moulines, "Continuous probabilistic transform for voice conversion, " IEEE Trans. Speech and Audio Processing, Vol. 6, No. 2, pp. 131-142, 1998.
9. T. Toda, A. Black, and K. Tokuda, "Voice conversion based on maximum likelihood estimation of spectral parameter trajectory, " IEEE Trans. Audio, Speech, Lang. Process., Vol. 15, No. 8, pp. 2222-2235, 2007.
10. E. Helander, T. Virtanen, J. Nurminen, and M. Gabbouj, "Voice conversion using partial least squares regression, " IEEE Trans. Audo, Speech, Lang. Process., Vol. 18, No. 5, pp. 912-921, 2010.
11. C. H. Lee and C. H. Wu, "Map-based adaptation for speech conversion using adaptation data selection and non-parallel training, " in Proc. INTERSPEECH, pp. 2254-2257, 2006.
12. D. Saito, S. Watanabe, A. Nakamura, N. Minematsu, "Voice conversion based on probabilistic integration of joint density model and speaker model, " in Proc. Acoustic Society of Japan, pp. 335- 338, 2010.
13. T. Toda, Y. Ohtani, and K. Shikano, "Eigenvoice conversion based on Gaussian mixture model, " in Proc. INTERSPEECH, pp. 2446 -2449, 2006.
14. D. Saito, K. Yamamoto, N. Minematsu, and K. Hirose, "One-tomany voice conversion based on tensor representation of speaker space, " in Proc. INTERSPEECH, pp. 653-656, 2011.
15. Z. H. Jian and Z. Yang, "Voice conversion using canonical correlation analysis based on gaussian mixture model, " SNPD, Vol. 1, pp. 210-215, 2007.
16. R. Takashima, T. Takiguchi, Y. Ariki, "Exemplar-based voice conversion in noisy environment, " SLT, pp.313-317, 2012.
17. S. Desai, E. V. Raghavendra, B. Yegnanarayana, A.W. Black, and K. Prahallad, "Voice conversion using artificial neural networks, " in Proc. ICASSP, pp. 3893-3896, 2009.
18. Y. J. Wu, H. Kawai, J. Ni, and R. H. Wang, "Minimum segmentation error based discriminative training for speech synthesis application, " in Proc. ICASSP 04, vol. 1, pp. 629-32, 2004.
19. E. McDermott, T. Hazen, J. L. Roux, A. Nakamura, and S. Katagiri, "Discriminative training for large vocabulary speech recognition using minimum classification error, " IEEE Transactions on Speech and Audio Processing, vol. 15, no. 1, pp. 203-223, 2007.
20. G. E. Hinton, S. Osindero, and Y. Teh, "A fast learning algorithm for deep belief nets, " Neural Computation, vol. 18, pp. 1527- 1554, 2006.
21. G. E. Hinton, S. Osindero, and Y. Teh, "A fast learning algorithm for deep belief nets, " Neural Computation, vol. 18, pp. 1527- 1554, 2006.
22. V. Nair and G. Hinton, "3-d object recognition with deep belief nets., " in To appear in Advances in Neural Information Processing Systems 22, 2009.
23. T Deselaers, S. Hasan, O. Bender, and H. Ney, "A deep learning approach to machine transliteration, " in Proc. EACLWorkshop on Statistical Machine Translation, 2009, pp. 233-241.
24. A. Mohamed, G. Dahl, and G. Hinton, "Acoustic Modeling using Deep Belief Networks, " IEEE Trans. on Audio, Speech, and Language Procesing, vol. 20, no. 1, pp. 14-22, 2012.
25. A. Kurematsu, K. Takeda, Y. Sagisaka, S. Katagiri, H. Kuwabara, and K.Shikano, "ATR Japanese speech database as a tool of speech recognition and synthesis, " Speech Communication, vol. 9, pp. 357-363, 1990.