Chenpeng Du

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 8 papers; trusts 154 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 143 citations into it; #13,203 of 35,345 by trust here, #17,412 by citations
• Signal Processing — 101 citations into it; #2,577 of 7,572 by trust here, #4,051 by citations
• Speech & Audio — 95 citations into it
• Generative Models — 37 citations into it
• Natural Language Processing — 29 citations into it
• Model Architectures — 16 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it

Whom Chenpeng Du trusts overall

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

1. Heiga Zen
2. Diederik P. Kingma
3. Sargur N. Srihari
4. Geoffrey E. Hinton
5. Guangzhi Sun
6. Jimmy Ba
7. Yoshua Bengio
8. Yu Zhang
9. Yi Ren
10. Jean-Luc Gauvain

Who trusts Chenpeng Du overall

1. Yiwei Guo
2. Feiyu Shen
3. K. Yu
4. Hyung-Seok Oh
5. Xie Chen
6. Sang-Hoon Lee
7. Zhichao Wu
8. Sanyuan Chen
9. Dongchao Yang
10. Rui Xue

Papers from Chenpeng Du's perspective

Ordered by how strongly the researchers Chenpeng Du 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• VQTTS: High-Fidelity Text-to-Speech Synthesis with Self-Supervised VQ Acoustic Feature (2022) — 68 citations
• UniCATS: A Unified Context-Aware Text-to-Speech Framework with Contextual VQ-Diffusion and Vocoding (2023) — 66 citations
• Towards Universal Speech Discrete Tokens: A Case Study for ASR and TTS (2023) — 48 citations
• Unsupervised Word-Level Prosody Tagging for Controllable Speech Synthesis (2022) — 16 citations
• Phone-Level Prosody Modelling With GMM-Based MDN for Diverse and Controllable Speech Synthesis (2021) — 24 citations
• Rich Prosody Diversity Modelling with Phone-Level Mixture Density Network (2021) — 18 citations
• Mixture Density Network for Phone-Level Prosody Modelling in Speech Synthesis (2021) — 8 citations
• Acoustic Word Embeddings for End-to-End Speech Synthesis (2021) — 4 citations