Yao Qian

Artificial Intelligence · 2001–2024

A researcher in the Science corpus: 12 papers; trusts 74 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 269 citations into it; #3,322 of 35,345 by trust here, #3,146 by citations
• Signal Processing — 173 citations into it; #1,487 of 7,572 by trust here, #570 by citations
• Speech & Audio — 137 citations into it; #305 of 1,076 by trust here, #197 by citations
• Natural Language Processing — 76 citations into it; #1,609 of 5,688 by trust here, #1,992 by citations
• Representation & Self-Supervised Learning — 44 citations into it
• Model Architectures — 30 citations into it
• Generative Models — 19 citations into it
• Evaluation & Benchmarks — 17 citations into it

Whom Yao Qian trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Heiga Zen
5. Diederik P. Kingma
6. Jimmy Ba
7. Ilya Sutskever
8. Alex Krizhevsky
9. J. Urgen Schmidhuber
10. Yann LeCun

Who trusts Yao Qian overall

1. Xu Tan
2. Zhizheng Wu
3. Zhaoxi Mu
4. Heiga Zen
5. Frank K. Soong
6. Yuchen Fan
7. Tao Qin
8. Benigno Uria
9. Oliver Watts
10. Xinyu Yang

Papers from Yao Qian's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• TTS synthesis with bidirectional LSTM based recurrent neural networks (2014) — 501 citations
• WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing (2021) — 3,371 citations
• UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data (2021) — 143 citations
• SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing (2021) — 297 citations
• On the training aspects of Deep Neural Network (DNN) for parametric TTS synthesis (2014) — 220 citations
• VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers (2024) — 206 citations
• Automatic prosody prediction and detection with Conditional Random Field (CRF) models (2010) — 54 citations
• Speech-Language Pre-Training for End-to-End Spoken Language Understanding (2021) — 54 citations
• Speaker and language factorization in DNN-based TTS synthesis (2016) — 31 citations
• Word embedding for recurrent neural network based TTS synthesis (2015) — 57 citations
• Multi-speaker modeling and speaker adaptation for DNN-based TTS synthesis (2015) — 132 citations
• Locating Boundaries for Prosodic Constituents in Unrestricted Mandarin Texts (2001) — 74 citations