| Speech synthesis based on hidden Markov models K Tokuda, Y Nankaku, T Toda, H Zen, J Yamagishi, K Oura Proceedings of the IEEE 101 (5), 1234-1252, 2013 | 562 | 2013 |
| An HMM-based singing voice synthesis system K Saino, H Zen, Y Nankaku, A Lee, K Tokuda Ninth International Conference on Spoken Language Processing, 2006 | 154 | 2006 |
| Recent development of the HMM-based singing voice synthesis system—Sinsy K Oura, A Mase, T Yamada, S Muto, Y Nankaku, K Tokuda Seventh ISCA Workshop on Speech Synthesis, 2010 | 129 | 2010 |
| State mapping based method for cross-lingual speaker adaptation in HMM-based speech synthesis YJ Wu, Y Nankaku, K Tokuda Tenth Annual Conference of the International Speech Communication Association, 2009 | 110 | 2009 |
| Singing Voice Synthesis Based on Deep Neural Networks. M Nishimura, K Hashimoto, K Oura, Y Nankaku, K Tokuda Interspeech, 2478-2482, 2016 | 103 | 2016 |
| An excitation model for HMM-based speech synthesis based on residual modeling R Maia, T Toda, H Zen, Y Nankaku, K Tokuda | 100 | 2007 |
| On the use of kernel PCA for feature extraction in speech recognition A Lima, H Zen, Y Nankaku, C Miyajima, K Tokuda, T Kitamura IEICE TRANSACTIONS on Information and Systems 87 (12), 2802-2811, 2004 | 92 | 2004 |
| Continuous stochastic feature mapping based on trajectory HMMs H Zen, Y Nankaku, K Tokuda IEEE Transactions on Audio, Speech, and Language Processing 19 (2), 417-430, 2010 | 85 | 2010 |
| The effect of neural networks in statistical parametric speech synthesis K Hashimoto, K Oura, Y Nankaku, K Tokuda 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 62 | 2015 |
| Product of experts for statistical parametric speech synthesis H Zen, MJF Gales, Y Nankaku, K Tokuda IEEE Transactions on Audio, Speech, and Language Processing 20 (3), 794-805, 2011 | 62 | 2011 |
| Singing voice synthesis based on generative adversarial networks Y Hono, K Hashimoto, K Oura, Y Nankaku, K Tokuda ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 61 | 2019 |
| Trajectory training considering global variance for speech synthesis based on neural networks K Hashimoto, K Oura, Y Nankaku, K Tokuda 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 40 | 2016 |
| HMM-based singing voice synthesis and its application to Japanese and English K Nakamura, K Oura, Y Nankaku, K Tokuda 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 40 | 2014 |
| Pitch adaptive training for HMM-based singing voice synthesis K Oura, A Mase, Y Nankaku, K Tokuda 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 38 | 2012 |
| Recent development of the DNN-based singing voice synthesis system—sinsy Y Hono, S Murata, K Nakamura, K Hashimoto, K Oura, Y Nankaku, ... 2018 Asia-Pacific Signal and Information Processing Association Annual …, 2018 | 37 | 2018 |
| Singing voice synthesis based on convolutional neural networks K Nakamura, K Hashimoto, K Oura, Y Nankaku, K Tokuda arXiv preprint arXiv:1904.06868, 2019 | 36 | 2019 |
| Face recognition based on separable lattice hmms D Kurata, Y Nankaku, K Tokuda, T Kitamura, Z Ghahramani 2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006 | 31 | 2006 |
| A trainable excitation model for HMM-based speech synthesis R Maia, T Toda, H Zen, Y Nankaku, K Tokuda Eighth Annual Conference of the International Speech Communication Association, 2007 | 29 | 2007 |
| Sinsy: A deep neural network-based singing voice synthesis system Y Hono, K Hashimoto, K Oura, Y Nankaku, K Tokuda IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 2803-2815, 2021 | 27 | 2021 |
| Voice activity detection based on conditional random fields using multiple features A Saito, Y Nankaku, A Lee, K Tokuda Eleventh Annual Conference of the International Speech Communication Association, 2010 | 26 | 2010 |
