| Speech enhancement based on deep denoising autoencoder. X Lu, Y Tsao, S Matsuda, C Hori Interspeech 2013, 436-440, 2013 | 1086 | 2013 |
| Speaker adaptive training using deep neural networks T Ochiai, S Matsuda, X Lu, C Hori, S Katagiri 2014 IEEE international conference on acoustics, speech and signal …, 2014 | 82 | 2014 |
| Ensemble modeling of denoising autoencoder for speech spectrum restoration. X Lu, Y Tsao, S Matsuda, C Hori Interspeech 14, 885-889, 2014 | 77 | 2014 |
| Context-dependent substroke model for HMM-based on-line handwriting recognition J Tokuno, N Inami, S Matsuda, M Nakai, H Shimodaira, S Sagayama Proceedings Eighth International Workshop on Frontiers in Handwriting …, 2002 | 55 | 2002 |
| CENSREC-1-AV: An audio-visual corpus for noisy bimodal speech recognition S Tamura, C Miyajima, N Kitaoka, T Yamada, S Tsuge, T Takiguchi, ... Training 720, 480, 2010 | 52 | 2010 |
| Sparse representation based on a bag of spectral exemplars for acoustic event detection X Lu, Y Tsao, S Matsuda, C Hori 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 50 | 2014 |
| Speech restoration based on deep learning autoencoder with layer-wised pretraining. X Lu, S Matsuda, C Hori, H Kashioka Interspeech 2012, 1504-1507, 2012 | 44 | 2012 |
| CENSREC-1-C: An evaluation framework for voice activity detection under noisy environments N Kitaoka, T Yamada, S Tsuge, C Miyajima, K Yamamoto, T Nishiura, ... Acoustical Science and Technology 30 (5), 363-371, 2009 | 41 | 2009 |
| CENSREC-4: development of evaluation framework for distant-talking speech recognition under reverberant environments. M Nakayama, T Nishiura, Y Denda, N Kitaoka, K Yamamoto, T Yamada, ... INTERSPEECH, 968-971, 2008 | 41 | 2008 |
| Multilingual speech-to-speech translation system: Voicetra S Matsuda, X Hu, Y Shiga, H Kashioka, C Hori, K Yasuda, H Okuma, ... 2013 IEEE 14th International Conference on Mobile Data Management 2, 229-233, 2013 | 40 | 2013 |
| A robust speech recognition system for communication robots in noisy environments CT Ishi, S Matsuda, T Kanda, T Jitsuhiro, H Ishiguro, S Nakamura, ... IEEE Transactions on Robotics 24 (3), 759-763, 2008 | 40 | 2008 |
| Factored language model based on recurrent neural network Y Wu, X Lu, H Yamamoto, S Matsuda, C Hori, H Kashioka Proceedings of COLING 2012, 2835-2850, 2012 | 36 | 2012 |
| Statistical acoustic model adaptation method, acoustic model learning method suitable for statistical acoustic model adaptation, storage medium storing parameters for building … S Matsuda, LU Xugang US Patent 10,629,185, 2020 | 34 | 2020 |
| Deep neural network learning method and apparatus, and category-independent sub-network learning apparatus S Matsuda, LU Xugang, C Hori, H Kashioka US Patent 9,691,020, 2017 | 32 | 2017 |
| Automatic node selection for deep neural networks using group lasso regularization T Ochiai, S Matsuda, H Watanabe, S Katagiri 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 31 | 2017 |
| Robust speech recognition system for communication robots in real environments CT Ishi, S Matsuda, T Kanda, T Jitsuhiro, H Ishiguro, S Nakamura, ... 2006 6th IEEE-RAS International Conference on Humanoid Robots, 340-345, 2006 | 31 | 2006 |
| Detecting robot-directed speech by situated understanding in physical interaction X Zuo, N Iwahashi, K Funakoshi, M Nakano, R Taguchi, S Matsuda, ... Information and Media Technologies 5 (4), 1314-1326, 2010 | 22 | 2010 |
| ATR parallel decoding based speech recognition system robust to noise and speaking styles S Matsuda, T Jitsuhiro, K Markov, S Nakamura IEICE transactions on Information and Systems 89 (3), 989-997, 2006 | 21 | 2006 |
| The NICT ASR system for IWSLT2012 H Yamamoto, Y Wu, CL Huang, X Lu, P Dixon, S Matsuda, C Hori, ... Proceedings of the 9th International Workshop on Spoken Language Translation …, 2012 | 20 | 2012 |
| Speech recognition system robust to noise and speaking styles. S Matsuda, T Jitsuhiro, K Markov, S Nakamura INTERSPEECH, 2817-2820, 2004 | 19 | 2004 |
