Tomohiro Nakatani

Signal Processing · 2008–2020

A researcher in the Science corpus: 19 papers; trusts 102 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 164 citations into it; #548 of 7,572 by trust here, #468 by citations
• Artificial Intelligence — 139 citations into it; #8,074 of 35,345 by trust here, #5,720 by citations
• Speech & Audio — 91 citations into it; #545 of 1,076 by trust here, #390 by citations
• Natural Language Processing — 33 citations into it
• Computational Mechanics — 32 citations into it; #1,857 of 10,001 by trust here, #4,178 by citations
• Computer Vision and Pattern Recognition — 25 citations into it
• Model Architectures — 20 citations into it
• Optimization & Training — 14 citations into it

Whom Tomohiro Nakatani trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Alex Graves
4. Emmanuel Vincent
5. Yoshua Bengio
6. Dong Yu
7. John R. Hershey
8. Jimmy Ba
9. Alex Krizhevsky
10. Shinji Watanabe

Who trusts Tomohiro Nakatani overall

1. Christoph Boeddeker
2. Nasser Mohammadiha
3. Donald S. Williamson
4. Lukas Drude
5. Shinji Watanabe
6. Naoyuki Kanda
7. Marc Delcroix
8. Yusuke Fujita
9. Mirco Ravanelli
10. Kurniawati Azizah

Papers from Tomohiro Nakatani's perspective

Ordered by how strongly the researchers Tomohiro Nakatani trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices (2015) — 250 citations
• The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech (2013) — 431 citations
• Improving Transformer-Based End-to-End Speech Recognition with Connectionist Temporal Classification and Language Model Integration (2019) — 231 citations
• Single Channel Target Speaker Extraction and Recognition with Speaker Beam (2018) — 204 citations
• Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures (2017) — 112 citations
• Noise Model Transfer: Novel Approach to Robustness Against Nonstationary Noise (2013) — 10 citations
• A method for fundamental frequency estimation and voicing decision: Application to infant utterances recorded in real acoustical environments (2008) — 75 citations
• SpeakerBeam: Speaker Aware Neural Network for Target Speaker Extraction in Speech Mixtures (2019) — 288 citations
• Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera (2012) — 88 citations
• Speech Dereverberation Based on Variance-Normalized Delayed Linear Prediction (2010) — 477 citations
• Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR (2020) — 46 citations
• Multimodal SpeakerBeam: Single Channel Target Speech Extraction with Audio-Visual Speaker Clues (2019) — 70 citations
• Speech Processing for Digital Home Assistants: Combining signal processing with deep-learning techniques (2019) — 152 citations
• Listening to Each Speaker One by One with Recurrent Selective Hearing Networks (2018) — 82 citations
• A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research (2016) — 398 citations
• Text-informed speech enhancement with deep neural networks (2015) — 32 citations
• LINEAR PREDICTION-BASED DEREVERBERATION WITH ADVANCED SPEECH ENHANCEMENT AND RECOGNITION TECHNOLOGIES FOR THE REVERB CHALLENGE (2014) — 112 citations
• Generalization of Multi-Channel Linear Prediction Methods for Blind MIMO Impulse Response Shortening (2012) — 274 citations
• Robust speech dereverberation based on non-negativity and sparse nature of speech spectrograms (2009) — 87 citations