Recent Development of the HMM-based Singing Voice Synthesis System - Sinsy

7th ISCA Workshop on Speech Synthesis, SSW 2010

Volumn , Issue , 2010, Pages 211-216

  Oura, Keiichiro ^a   Mase, Ayami ^a   Yamada, Tomohiko ^a   Muto, Satoru ^a   Nankaku, Yoshihiko ^a   Tokuda, Keiichi ^a  

^a NAGOYA INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

HMM based speech synthesis; singing voice synthesis

Indexed keywords

MUSIC; SPEECH SYNTHESIS;

CONTEXT DEPENDENT; HIDDEN MARKOV MODEL-BASED SPEECH SYNTHESIS; HIDDEN-MARKOV MODELS; MODEL-BASED OPC; PARAMETRIC APPROACH; SINGING VOICES; SINGING-VOICE SYNTHESIS; SPECTRA'S; SYNTHESISED; WAVEFORMS;

HIDDEN MARKOV MODELS;

EID: 84876667508     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. T. Yoshimura, K. Tokuda, T. Masuko, T. Kobayashi, and T. Kitamura, “Simultaneous Modeling of Spectrum, Pitch and Duration in HMM-Based Speech Synthesis,” Proc. of Eurospeech, pp. 2347-2350, 1999.
2. J. Yamagishi, “Average-Voice-Based Speech Synthesis,” Ph. D. thesis, Tokyo Institute of Technology, 2006.
3. T. Yoshimura, K. Tokuda, T. Masuko, T. Kobayashi, and T. Kitamura, “Speaker Interpolation in HMM-Based Speech Synthesis System,” Proc. of Eurospeech, pp. 2523-2526, 1997.
4. K. Shichiri, A. Sawabe, K. Tokuda, T. Masuko, T. Kobayashi, and T. Kitamura, “Eigenvoices for HMM-Based Speech Synthesis,” Proc. of ICSLP, pp. 1269-1272, 2002.
5. K. Saino, H. Zen, Y. Nankaku, A. Lee, and K. Tokuda, “An HMM-Based Singing Voice Synthesis System,” Proc. of ICSLP, pp. 1141-1144, 2006.
6. HMM-Based Singing Voice Synthesis System (Sinsy), http://www.sinsy.jp/ (in Japanese).
7. HMM-Based Speech Synthesis System (HTS), http://hts.sp.nitech.ac.jp/.
8. HMM-Based Speech Synthesis Engine (hts engine API), http://hts-engine.sourceforge.net/.
9. Speech Signal Processing Toolkit (SPTK), http://sptk.sourceforge.net/.
10. A Speech Analysis, Modification and Synthesis System (STRAIGHT), http://www.wakayama-u.ac.jp/kawahara/STRAIGHTadv/indexe.html.
11. CrestMuseXML Toolkit (CMX), http://cmx.sourceforge.jp/.
12. MusicXML Definition, http://musicxml.org/.
13. K. Tokuda, T. Kobayashi, T. Chiba, and S. Imai, “Spectral Estimation of Speech by Mel-Generalized Cepstral Analysis,” IEICE Trans. vol. 75-A, no. 7, pp. 1124-1134, 1992.
14. K. Tokuda, T. Yoshimura, T. Masuko, T. Kobayashi, and T. Kitamura, “Speech Parameter Generation Algorithms for HMM-Based Speech Synthesis,” Proc. of ICASSP, pp. 1315-1318, 2000.
15. S. Imai, “Cepstral Analysis Synthesis on the Mel Frequency Scale,” Proc. of ICASSP, pp. 93-96, 1983.
16. H. Zen, T. Masuko, K. Tokuda, T. Kobayashi, and T. Kitamura, “A Hidden Semi-Markov Model-Based Speech Synthesis System,” Proc. of IEICE Trans. Inf. & Sys., vol. 90D, no. 5, pp. 825-834, 2007.
17. K. Oura, H. Zen, Y. Nankaku, A. Lee, and K. Tokuda, “A Fully Consistent Hidden Semi-Markov Model-Based Speech Recognition System,” Proc. of IEICE Trans. Inf. and Syst., vol. E91-D, no. 11, pp. 2693-2700, 208.
18. A. Kuramatsu, K. Takeda, Y. Sagisaka, S. Katagiri, H. Kawabara, and K. Shikano, “ATR Japanese Speech Database as a Tool of Speech Recognition and Synthesis,” Speech Communication, vol. 9, pp. 357-363, 1990.
19. A. Mase, K. Oura, Y. Nankaku, and K. Tokuda, “HMM-Based Singing Voice Synthesis System Using Pitch-Shifted Pseudo Training Data,” Proc. of Interspeech, 2010 (to be published).
20. K. Shinoda and T. Watanabe, “MDL-Based Context-Dependent Subword Modeling for Speech Recognition,” J. Acoust. Soc. Jpn.(E), vol.21, no. 2, pp. 79-86, 2000.
21. T. Yamada, S. Muto, Y. Nankaku, S. Sako, and K. Tokuda, “Vibrato Modeling for HMM-Based Singing Voice Synthesis,” Proc. of Information Processing Society of Japan, vol. 2009-MUS-80, no. 5, pp. 1-6, 2009 (in Japanese).
22. T. Nakano, M. Goto, and Y. Hiraga, “An Automatic Singing Skill Evaluation Method for Unknown Melodies Using Pitch Interval Accuracy and Vibrato Features”, Proc. of Interspeech, pp. 1706-1709, 2006.
23. J. Sundberg, “The Science of the Singing Voice,” Northern Illinois University Press, 1987.
24. C. E. Seashore, “A Musical Ornament, the Vibrato,” Proc. of Psychology of Music, McGraw-Hill Book Company, pp. 33-52, 1938.
25. S. Muto, K. Oura, Y. Nankaku, and K. Tokuda, “Reducing Computational Cost of Training for HMM-Based Singing Voice Synthesis Using Note Boundaries,” Proc. of Acoustic Society of Japan Spring Meeting, vol. I, 2-7-8, pp. 347-348, 2009 (in Japanese).
26. A New and Simplified BSD License, http://www.opensource.org/licenses/bsd-license.php.
27. H. Kawahara, M. K. Ikuyo, and A. Cheneigne, “Restructuring Speech Representations Using a Pitch-Adaptive Time-Frequency Smoothing and an Instantaneous-Frequency-Based F0 Extraction: Possible Role of a Repetitive Structure in Sounds,” Proc. of Speech Communication, 27, pp. 187-207, 1999.
28. H. Zen, K. Oura, T. Nose, J. Yamagishi, S. Sako, T. Toda, T. Masuko, A. W. Black, and K. Tokuda, “Recent Development of the HMM-Based Speech Synthesis System (HTS),” Proc. of APSIPA, pp. 121-130, 2009.
29. The Hidden Markov Model Toolkit (HTK), http://htk.eng.cam.ac.uk/.
30. T. Kitahara and H. Katayose, “On CrestMuseXML (CMX) Toolkit Ver. 0.40,” IPSJ SIG Technical Report, vol. 2008-MUS-75, no. 17, pp. 95-100, 2008 (in Japanese).
31. K. Tokuda, T. Masuko, N. Miyazaki, and T. Kobayashi, “Hidden Markov Models Based on Multi-Space Probability Distribution for Pitch Pattern Modeling,” Proc. of ICASSP, vol. I, pp. 229-232, 1999.
32. Y. J. Wu, and R. H. Wang, “Minimum Generation Error Training for HMM-Based Speech Synthesis,” Proc. of ICASSP, vol. I, pp. 89-92, 2006.
33. T. Toda and K. Tokuda, “Speech Parameter Generation Algorithm Considering Global Variance for HMM-Based Speech Synthesis,” Proc. of Interspeech, pp. 2801-2804, 2005.