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Atsunori Ogawa
Researcher at Nippon Telegraph and Telephone
Publications - 161
Citations - 2086
Atsunori Ogawa is an academic researcher from Nippon Telegraph and Telephone. The author has contributed to research in topics: Acoustic model & Speech enhancement. The author has an hindex of 21, co-authored 145 publications receiving 1646 citations. Previous affiliations of Atsunori Ogawa include Spacelabs Healthcare & Nagoya University.
Papers
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Proceedings ArticleDOI
The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices
Takuya Yoshioka,Nobutaka Ito,Marc Delcroix,Atsunori Ogawa,Keisuke Kinoshita,Masakiyo Fujimoto,Chengzhu Yu,Wojciech J. Fabian,Miquel Espi,Takuya Higuchi,Shoko Araki,Tomohiro Nakatani +11 more
TL;DR: NTT's CHiME-3 system is described, which integrates advanced speech enhancement and recognition techniques, which achieves a 3.45% development error rate and a 5.83% evaluation error rate.
Proceedings ArticleDOI
Improving transformer-based end-to-end speech recognition with connectionist temporal classification and language model integration
TL;DR: This work integrates connectionist temporal classification (CTC) with Transformer for joint training and decoding of automatic speech recognition (ASR) tasks and makes training faster than with RNNs and assists LM integration.
Proceedings ArticleDOI
Single Channel Target Speaker Extraction and Recognition with Speaker Beam
TL;DR: This paper addresses the problem of single channel speech recognition of a target speaker in a mixture of speech signals by exploiting auxiliary speaker information provided by an adaptation utterance from the target speaker to extract and recognize only that speaker.
Proceedings ArticleDOI
Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures.
Kateřina Žmolíková,Marc Delcroix,Keisuke Kinoshita,Takuya Higuchi,Atsunori Ogawa,Tomohiro Nakatani +5 more
TL;DR: This work uses a neural network to estimate masks to extract the target speaker and derive beamformer filters using these masks, in a similar way as the recently proposed approach for extraction of speech in presence of noise.
Journal ArticleDOI
Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera
Takaaki Hori,Shoko Araki,Takuya Yoshioka,Masakiyo Fujimoto,Shinji Watanabe,Takanobu Oba,Atsunori Ogawa,Kazuhiro Otsuka,Dan Mikami,Keisuke Kinoshita,Tomohiro Nakatani,Atsushi Nakamura,Junji Yamato +12 more
TL;DR: The techniques and the attempt to achieve the low-latency monitoring of meetings are described, the experimental results for real-time meeting transcription are shown, and the goal is to recognize automatically “who is speaking what” in an online manner for meeting assistance.