| Discriminative training for large-vocabulary speech recognition using minimum classification error E McDermott, TJ Hazen, J Le Roux, A Nakamura, S Katagiri IEEE Transactions on Audio, Speech, and Language Processing 15 (1), 203-223, 2006 | 213 | 2006 |
| Efficient WFST-based one-pass decoding with on-the-fly hypothesis rescoring in extremely large vocabulary continuous speech recognition T Hori, C Hori, Y Minami, A Nakamura IEEE Transactions on audio, speech, and language processing 15 (4), 1352-1365, 2007 | 177 | 2007 |
| Deformation structures in Ti-rich TiAl polysynthetically twinned crystals H Inui, A Nakamura, MH Oh, M Yamaguchi Philosophical Magazine A 66 (4), 557-573, 1992 | 167 | 1992 |
| Linear prediction-based dereverberation with advanced speech enhancement and recognition technologies for the REVERB challenge M Delcroix, T Yoshioka, A Ogawa, Y Kubo, M Fujimoto, N Ito, K Kinoshita, ... Reverb workshop, 2014 | 121 | 2014 |
| Variational Bayesian estimation and clustering for speech recognition S Watanabe, Y Minami, A Nakamura, N Ueda IEEE Transactions on Speech and Audio Processing 12 (4), 365-381, 2004 | 107 | 2004 |
| Low-latency real-time meeting recognition and understanding using distant microphones and omni-directional camera T Hori, S Araki, T Yoshioka, M Fujimoto, S Watanabe, T Oba, A Ogawa, ... IEEE transactions on audio, speech, and language processing 20 (2), 499-513, 2011 | 100 | 2011 |
| A speech and language database for speech translation research T Morimoto, N Uratani, T Takezawa, O Furuse, Y Sobashima, H Iida, ... Third International Conference on Spoken Language Processing, 1994 | 99 | 1994 |
| High-resolution electron microscope study of lamellar boundaries in Ti-rich TiAl polysynthetically twinned crystals H Inui, A Nakamura, MH Oh, M Yamaguchi Ultramicroscopy 39 (1-4), 268-278, 1991 | 94 | 1991 |
| Japanese speech databases for robust speech recognition A Nakamura, S Matsunaga, T Shimizu, M Tonomura, Y Sagisaka Proceeding of Fourth International Conference on Spoken Language Processing …, 1996 | 83 | 1996 |
| A rapid PCR-aided selection of a rice line containing the Rf-1 gene which is involved in restoration of the cytoplasmic male sterility N Ichikawa, N Kishimoto, A Inagaki, A Nakamura, Y Koshino, Y Yokozeki, ... Molecular Breeding 3 (3), 195-202, 1997 | 73 | 1997 |
| Genetic diagnosis of cytoplasmic male sterile cybrid plants of rice H Akagi, A Nakamura, R Sawada, M Oka, T Fujimura Theoretical and applied genetics 90 (7), 948-951, 1995 | 70 | 1995 |
| Is speech enhancement pre-processing still relevant when using deep neural networks for acoustic modeling? M Delcroix, Y Kubo, T Nakatani, A Nakamura Interspeech, 2992-2996, 2013 | 54 | 2013 |
| Determination of glyoxal, methylglyoxal, diacethyl, and 2, 3-pentanedione in fermented foods by high-performance liquid chromatography with fluorescence detection M Yamaguchi, J Ishida, ZX Xuan, A Nakamura, T Yoshitake Journal of Liquid Chromatography & Related Technologies 17 (1), 203-211, 1994 | 53 | 1994 |
| Structural homology between semidwarfism-related proteins and glutelin seed protein in rice (Oryza sativa L.) H Hirano, S Komatsu, A Nakamura, F Kikuchi, H Kajiwara, S Tsunasawa, ... Theoretical and Applied Genetics 83 (2), 153-158, 1991 | 51 | 1991 |
| Application of variational Bayesian approach to speech recognition S Watanabe, Y Minami, A Nakamura, N Ueda Advances in Neural Information Processing Systems 15, 2002 | 50 | 2002 |
| Generalized fast on-the-fly composition algorithm for WFST-based speech recognition. T Hori, A Nakamura INTERSPEECH, 557-560, 2005 | 47 | 2005 |
| Discriminative training based on an integrated view of MPE and MMI in margin and error space E McDermott, S Watanabe, A Nakamura 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 41 | 2010 |
| Cold-rolling of Ti-rich TiAl polysynthetically twinned crystals SR Nishitani, MH Oh, A Nakamura, T Fujiwara, M Yamaguchi Journal of Materials Research 5 (3), 484-487, 1990 | 41 | 1990 |
| Real-time one-pass decoding with recurrent neural network language model for speech recognition T Hori, Y Kubo, A Nakamura 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 39 | 2014 |
| Speech recognition in the presence of highly non-stationary noise based on spatial, spectral and temporal speech/noise modeling combined with dynamic variance adaptation M Delcroix, K Kinoshita, T Nakatani, S Araki, A Ogawa, T Hori, ... Machine Listening in Multisource Environments, 2011 | 37 | 2011 |
Shinji WatanabeCarnegie Mellon UniversityVerified email at cmu.edu
