Takuya Yoshioka
Artificial Intelligence · 2009–2023
A researcher in the Science corpus: 25 papers; trusts 177 researchers and is trusted by 52 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 353 citations into it; #6,666 of 35,345 by trust here, #4,231 by citations
- Signal Processing — 327 citations into it; #465 of 7,572 by trust here, #336 by citations
- Speech & Audio — 168 citations into it; #352 of 1,076 by trust here, #203 by citations
- Computer Vision and Pattern Recognition — 100 citations into it
- Natural Language Processing — 71 citations into it
- Computational Mechanics — 55 citations into it; #1,547 of 10,001 by trust here, #3,029 by citations
- Evaluation & Benchmarks — 48 citations into it; #1,927 of 3,147 by trust here, #2,166 by citations
- Model Architectures — 48 citations into it
Whom Takuya Yoshioka trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Dong Yu
- Abdel-rahman Mohamed
- George E. Dahl
- Yi Luo
- Yoshua Bengio
- Diederik P. Kingma
- Li Deng
- Zhuo Chen
- Alex Graves
Who trusts Takuya Yoshioka overall
- Sanyuan Chen
- Donald S. Williamson
- Christoph Boeddeker
- Mirco Ravanelli
- Zhuo Chen
- Lukas Drude
- Shinji Watanabe
- Yu Wu
- Jinyu Li
- Dong Yu
Papers from Takuya Yoshioka's perspective
Ordered by how strongly the researchers Takuya Yoshioka trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- 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
- Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation (2019) — 972 citations
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing (2021) — 3,371 citations
- The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech (2013) — 431 citations
- Investigation of unsupervised adaptation of DNN acoustic models with filter bank input (2014) — 46 citations
- Noise Model Transfer: Novel Approach to Robustness Against Nonstationary Noise (2013) — 10 citations
- Don’t Shoot Butterfly with Rifles: Multi-Channel Continuous Speech Separation with Early Exit Transformer (2020) — 35 citations
- Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera (2012) — 88 citations
- Continuous Speech Separation: Dataset and Analysis (2020) — 256 citations
- Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement (2021) — 28 citations
- Speech Dereverberation Based on Variance-Normalized Delayed Linear Prediction (2010) — 477 citations
- SpeechX: Neural Codec Language Model as a Versatile Speech Transformer (2023) — 123 citations
- i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data (2023) — 4 citations
- ICASSP 2023 Deep Noise Suppression Challenge (2023) — 193 citations
- Ultra Fast Speech Separation Model with Teacher Student Learning (2021) — 15 citations
- Personalized speech enhancement: new models and Comprehensive evaluation (2021) — 82 citations
- Investigation of Practical Aspects of Single Channel Speech Separation for ASR (2021) — 21 citations
- Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone (2021) — 53 citations
- End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation (2019) — 217 citations
- Multi-Microphone Neural Speech Separation for Far-Field Multi-Talker Speech Recognition (2018) — 121 citations