|Positional cloning of the rice Rf-1 gene, a restorer of BT-type cytoplasmic male sterility that encodes a mitochondria-targeting PPR protein|
H Akagi, A Nakamura, Y Yokozeki-Misono, A Inagaki, H Takahashi, ...
Theoretical and Applied Genetics 108 (8), 1449-1457, 2004
|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, 2007
|A codominant DNA marker closely linked to the rice nuclear restorer gene, Rf-1, identified with inter-SSR fingerprinting|
H Akagi, Y Yokozeki, A Inagaki, A Nakamura, T Fujimura
Genome 39 (6), 1205-1209, 1996
|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
|Increased expression of co-chaperone HOP with HSP90 and HSC70 and complex formation in human colonic carcinoma|
H Kubota, S Yamamoto, E Itoh, Y Abe, A Nakamura, Y Izumi, H Okada, ...
Cell Stress and Chaperones 15 (6), 1003-1011, 2010
|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
|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
|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
|Infrared microspectroscopy analysis of water distribution in deformed and metamorphosed rocks|
S Nakashima, H Matayoshi, T Yuko, K Michibayashi, T Masuda, N Kuroki, ...
Tectonophysics 245 (3-4), 263-276, 1995
|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
|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
|Vehicle display device|
T Masuda, K Yamamoto, K Hijikata, S Satomura, H Oishi, T Sunaguchi, ...
US Patent 7,772,970, 2010
|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 (7-8), 948-951, 1995
|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
|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
|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
|Application of variational Bayesian approach to speech recognition|
S Watanabe, Y Minami, A Nakamura, N Ueda
Advances in Neural Information Processing Systems, 1261-1268, 2003
|Generalized fast on-the-fly composition algorithm for WFST-based speech recognition|
T Hori, A Nakamura
Ninth European Conference on Speech Communication and Technology, 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
|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