Naoyuki Kanda
Artificial Intelligence · 2013–2023
A researcher in the Science corpus: 12 papers; trusts 181 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 325 citations into it; #6,773 of 35,345 by trust here, #6,266 by citations
- Signal Processing — 236 citations into it; #1,055 of 7,572 by trust here, #741 by citations
- Speech & Audio — 174 citations into it; #639 of 1,076 by trust here, #368 by citations
- Computer Vision and Pattern Recognition — 94 citations into it
- Natural Language Processing — 69 citations into it; #1,828 of 5,688 by trust here, #3,282 by citations
- Evaluation & Benchmarks — 39 citations into it
- Model Architectures — 38 citations into it
- Computational Mechanics — 22 citations into it
Whom Naoyuki Kanda trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Daniel Povey
- Dong Yu
- Alex Graves
- Frank Torsten Bernd Seide
- Yoshua Bengio
- Alex Krizhevsky
- Sepp Hochreiter
- George E. Dahl
- Tom Ko
Who trusts Naoyuki Kanda overall
- Shinji Watanabe
- Takaaki Hori
- Jinyu Li
- Yusuke Fujita
- Ekin Dogus Cubuk
- Shota Horiguchi
- Hervé Bredin
- Anton Ragni
- Mark John Francis Gales
- Rohit Prabhavalkar
Papers from Naoyuki Kanda's perspective
Ordered by how strongly the researchers Naoyuki Kanda trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Elastic spectral distortion for low resource speech recognition with deep neural networks (2013) — 129 citations
- WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing (2021) — 3,371 citations
- A Review of Speaker Diarization: Recent Advances with Deep Learning (2021) — 437 citations
- End-to-End Neural Speaker Diarization with Permutation-Free Objectives (2019) — 312 citations
- Maximum a posteriori Based Decoding for CTC Acoustic Models (2016) — 44 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
- Speech-Language Pre-Training for End-to-End Spoken Language Understanding (2021) — 54 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
- Acoustic Modeling for Distant Multi-talker Speech Recognition with Single- and Multi-channel Branches (2019) — 45 citations
- Lattice-free State-level Minimum Bayes Risk Training of Acoustic Models (2018) — 29 citations