Naoyuki Kanda
Title
Cited by
Cited by
Year
Elastic spectral distortion for low resource speech recognition with deep neural networks
N Kanda, R Takeda, Y Obuchi
Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on …, 2013
642013
A two-layer model for behavior and dialogue planning in conversational service robots
M Nakano, Y Hasegawa, K Nakadai, T Nakamura, J Takeuchi, T Torii, ...
2005 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2005
602005
Multi-domain spoken dialogue system with extensibility and robustness against speech recognition errors
K Komatani, N Kanda, M Nakano, K Nakadai, H Tsujino, T Ogata, ...
Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue, 9-17, 2009
442009
Open-vocabulary keyword detection from super-large scale speech database
N Kanda, H Sagawa, T Sumiyoshi, Y Obuchi
2008 IEEE 10th Workshop on Multimedia Signal Processing, 939-944, 2008
382008
A multi-expert model for dialogue and behavior control of conversational robots and agents
M Nakano, Y Hasegawa, K Funakoshi, J Takeuchi, T Torii, K Nakadai, ...
Knowledge-Based Systems 24 (2), 248-256, 2011
372011
Maximum a posteriori Based Decoding for CTC Acoustic Models
N Kanda, X Lu, H Kawai
Interspeech 2016, 1868-1872, 2016
322016
The Hitachi/JHU CHiME-5 system: Advances in speech recognition for everyday home environments using multiple microphone arrays
N Kanda, R Ikeshita, S Horiguchi, Y Fujita, K Nagamatsu, X Wang, ...
The 5th International Workshop on Speech Processing in Everyday Environments …, 2018
202018
Contextual constraints based on dialogue models in database search task for spoken dialogue systems
K Komatani, N Kanda, T Ogata, HG Okuno
Proc. European Conf. Speech Commun. & Tech.(EUROSPEECH), 877-880, 2005
192005
Investigation of lattice-free maximum mutual information-based acoustic models with sequence-level Kullback-Leibler divergence
N Kanda, Y Fujita, K Nagamatsu
2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 69-76, 2017
172017
Lattice-free State-level Minimum Bayes Risk Training of Acoustic Models
N Kanda, Y Fujita, K Nagamatsu
Interspeech 2018, 2923-2927, 2018
142018
多段リスコアリングに基づく大規模音声中の任意検索語検出
神田直之, 住吉貴志, 小窪浩明, 佐川浩彦, 大淵康成
電子情報通信学会論文誌 D 95 (4), 969-981, 2012
122012
マルチドメイン音声対話システムにおける対話履歴を利用したドメイン選択
神田直之, 駒谷和範, 中野幹生, 中臺一博, 辻野広司, 尾形哲也, 奥乃博
情報処理学会論文誌 48 (5), 1980-1989, 2007
102007
The NICT asr system for IWSLT 2014
P Shen, X Lu, X Hu, N Kanda, M Saiko, C Hori
Proceedings of IWSLT, 113-118, 2014
92014
End-to-end neural speaker diarization with permutation-free objectives
Y Fujita, N Kanda, S Horiguchi, K Nagamatsu, S Watanabe
arXiv preprint arXiv:1909.05952, 2019
82019
Minimum Bayes risk training of CTC acoustic models in maximum a posteriori based decoding framework
N Kanda, X Lu, H Kawai
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
82017
Training data pseudo-shuffling and direct decoding framework for recurrent neural network based acoustic modeling
N Kanda, M Tachimori, X Lu, H Kawai
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015
82015
Sequence distillation for purely sequence trained acoustic models
N Kanda, Y Fujita, K Nagamatsu
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
72018
Boundary contraction training for acoustic models based on discrete deep neural networks
R Takeda, N Kanda, N Nukaga
Fifteenth Annual Conference of the International Speech Communication …, 2014
72014
End-to-End Neural Speaker Diarization with Self-attention
Y Fujita, N Kanda, S Horiguchi, Y Xue, K Nagamatsu, S Watanabe
arXiv preprint arXiv:1909.06247, 2019
62019
Maximum-a-Posteriori-Based Decoding for End-to-End Acoustic Models
N Kanda, X Lu, H Kawai
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (5), 1023 …, 2017
62017
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Articles 1–20