The HMM-based speech synthesis system (HTS) version 2.0 H Zen, T Nose, J Yamagishi, S Sako, T Masuko, AW Black, K Tokuda SSW, 294-299, 2007 | 681 | 2007 |
Robust speaker-adaptive HMM-based text-to-speech synthesis J Yamagishi, T Nose, H Zen, ZH Ling, T Toda, K Tokuda, S King, S Renals IEEE Transactions on Audio, Speech, and Language Processing 17 (6), 1208-1230, 2009 | 247 | 2009 |
A style control technique for HMM-based expressive speech synthesis T Nose, J Yamagishi, T Masuko, T Kobayashi IEICE transactions on information and systems 90 (9), 1406-1413, 2007 | 168 | 2007 |
The HMM-based speech synthesis system (HTS) K Tokuda http://hts. sp. nitech. ac. jp/, 2010 | 82 | 2010 |
Statistical parametric speech synthesis based on Gaussian process regression T Koriyama, T Nose, T Kobayashi IEEE journal of selected topics in Signal Processing 8 (2), 173-183, 2013 | 57 | 2013 |
HMM-based style control for expressive speech synthesis with arbitrary speaker's voice using model adaptation T NOSE, M TACHIBANA, T KOBAYASHI IEICE transactions on information and systems 92 (3), 489-497, 2009 | 56 | 2009 |
Recent development of the HMM-based speech synthesis system (HTS) H Zen, K Oura, T Nose, J Yamagishi, S Sako, T Toda, T Masuko, ... | 53 | 2009 |
An intuitive style control technique in HMM-based expressive speech synthesis using subjective style intensity and multiple-regression global variance model T Nose, T Kobayashi Speech Communication 55 (2), 347-357, 2013 | 35 | 2013 |
Construction and analysis of phonetically and prosodically balanced emotional speech database E Takeishi, T Nose, Y Chiba, A Ito 2016 Conference of The Oriental Chapter of International Committee for …, 2016 | 32 | 2016 |
The HMM-based speech synthesis system (HTS) Version 2.1 K Tokuda, H Zen, J Yamagishi, T Masuko, S Sako, A Black, T Nose Online: http://hts. sp. nitech. ac. jp/, accessed 27, 2008 | 27 | 2008 |
Speaker and style adaptation using average voice model for style control in HMM-based speech synthesis M Tachibana, S Izawa, T Nose, T Kobayashi Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE …, 2008 | 25 | 2008 |
Style estimation of speech based on multiple regression hidden semi-Markov model T Nose, Y Kato, T Kobayashi INTERSPEECH, 2285-2288, 2007 | 23 | 2007 |
A speaker adaptation technique for MRHSMM-based style control of synthetic speech T Nose, Y Kato, T Kobayashi ICASSP (4), 833-836, 2007 | 23 | 2007 |
HMM-based emphatic speech synthesis using unsupervised context labeling. Y Maeno, T Nose, T Kobayashi, Y Ijima, H Nakajima, H Mizuno, ... INTERSPEECH, 1849-1852, 2011 | 22 | 2011 |
On the use of extended context for HMM-based spontaneous conversational speech synthesis T Koriyama, T Nose, T Kobayashi INTERSPEECH, 2657-2660, 2011 | 22 | 2011 |
Automatic assessment of English proficiency for Japanese learners without reference sentences based on deep neural network acoustic models J Fu, Y Chiba, T Nose, A Ito Speech Communication 116, 86-97, 2020 | 21 | 2020 |
A technique for controlling voice quality of synthetic speech using multiple regression HSMM M Tachibana, T Nose, J Yamagishi, T Kobayashi INTERSPEECH, 2006 | 21 | 2006 |
A style control technique for speech synthesis using multiple regression HSMM T Nose, J Yamagishi, T Kobayashi ICSLP 2, 5, 2006 | 21 | 2006 |
Propagation in ROF road-vehicle communication system using millimeter wave K Sato, M Fujise, R Tachita, E Hase, T Nose IVEC2001. Proceedings of the IEEE International Vehicle Electronics …, 2001 | 20 | 2001 |
Comparison of speech recognition performance between Kaldi and Google cloud speech API T Kimura, T Nose, S Hirooka, Y Chiba, A Ito Recent Advances in Intelligent Information Hiding and Multimedia Signal …, 2019 | 19 | 2019 |