I am a Ph.D. student of Zhejiang University, supervised by Prof. Siliang Tang（汤斯亮） and Prof. Yueting Zhuang（庄越挺）. I obtained my B.S. degree at Zhejiang University. I also collaborate with Xu Tan (谭旭) from Microsoft Research Asia and Lingfei Wu (吴凌飞) closely.

My research interest includes Text-to-Speech Synthesis, ASR Error Correction, Graph Neural Network and Neural Machine Translation. I have published 10+ papers includes ICML, ICLR, NeurIPS, EMNLP, IJCAI, et.al.

I have developed the first large-scale non-autoregressive text-to-Speech synthesis system NaturalSpeech 2 and the advanced version NaturalSpeech 3.

I am the main contributor of Graph4NLP project. I am one of the book chapter contributors of the book “Graph Neural Networks: Foundations, Frontiers, and Applications”.

I am expected to graduate in June 2024 and seeking job opportunities. Please feel free to contact me if you are interested!

🔥 News

• 2024.05: 🎉 NaturalSpeech 3 is accepted by ICML2024!
• 2024.03: 🎉 We are delighted to released NaturalSpeech 3, which is a advanced version of NaturalSpeech series with speech factorization.
• 2024.01: 🎉 NaturalSpeech 2 and PromptTTS 2 are accepted by ICLR2024 for Spotlight and Poster presentation!
• 2023.09: 🎉 We released PromptTTS 2, which is a large-scale TTS system using text prompt.
• 2023.04: 🎉 We are delighted to release our NaturalSpeech 2, which is the first large-scale NAR TTS system. It can generate high-quality speech with only a 3-second prompt!
• 2021/06: 🎉 Check out our most recent survey paper, titled “Graph Neural Networks for Natural Language Processing: A Survey”! First comprehensive survey on GNNs for NLP!
• 2021.06: 🔥 We are delighted to release our Graph4NLP Library (⭐️1.6k+), which is the first library for the easy use of GNNs for NLP!

📝 Publications

🎙 Speech Synthesis

ICML 2024

NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju*, Yuancheng Wang*, Kai Shen*, Xu Tan*, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao

Project

• NaturalSpeech 3 is the advanced version of NaturalSpeech serials with speech factorization.

ICLR 2024 Spotlight

Naturalspeech 2: Latent diffusion models are natural and zero-shot speech and singing synthesizers
Kai Shen*, Zeqian Ju*, Xu Tan*, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian

Project

• NaturalSpeech 2 is the first large-scale non-autoregressive text-to-speech synthesis system. It can generate high-quality speech with only a 3-second prompt!

• ICLR 2024 PromptTTS 2: Describing and Generating Voices with Text Prompt, Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
• EMNLP 2023 Mask the correct tokens: An embarrassingly simple approach for error correction, Kai Shen, Yichong Leng, Xu Tan, Siliang Tang, Yuan Zhang, Wenjie Liu, Edward Lin

📚 Machine Translation

• Work in Progress A Study on ReLU and Softmax in Transformer, Kai Shen, Junliang Guo, Xu Tan, Siliang Tang, Rui Wang, Jiang Bian

🧑‍🎨 Graph Neural Network

Foundations and Trends in Machine Learning

DLG4NLP Project

Survey Paper: Graph neural networks for natural language processing: A survey
Lingfei Wu, Yu Chen, Kai Shen(First Student Author), Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long

Graph4NLP Library | , most important contributor

• DLG4NLP consists: 1) the most comprehensive survey paper on GNNs for NLP; 2) a library for the easy use of GNNs for NLP.

• NeurIPS 2021 Learning to Generate Visual Questions with Noisy Supervision, Kai Shen, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhuoye Ding, Yun Xiao, Bo Long
• Under Review Ask Question with Double Hints: Visual Question Generation with Answer-awareness and Region-reference, Kai Shen, Lingfei Wu, Siliang Tang, Fangli Xu, Zhu Zhang, Yu Qiang, Yueting Zhuang
• IJCAI 2020 Hierarchical Attention Based Spatial-Temporal Graph-to-Sequence Learning for Grounded Video Description, Kai Shen, Lingfei Wu, Fangli Xu, Siliang Tang, Jun Xiao, Yueting Zhuang
• Graph Neural Networks: Foundations, Frontiers, and Applications Graph Neural Networks in Computer Vision, Siliang Tang, Wenqiao Zhang, Zongshen Mu, Kai Shen, Juncheng Li, Jiacheng Li, Lingfei Wu

Others

• Preprint Scenario-based Multi-product Advertising Copywriting Generation for E-Commerce, Xueying Zhang, Kai Shen, Chi Zhang, Xiaochuan Fan, Yun Xiao, Zhen He, Bo Long, Lingfei Wu

🎖 Honors and Awards

• 2020-2021 National Scholarship (Top 1%)
• 2017-2018 The Third Prize Scholarship (Top 20%)
• 2016-2017 The Third Prize Scholarship (Top 20%)
• 2015-2016 The Second Prize Scholarship (Top 8%)

📖 Educations

• 2019.06 - 2024.06, Ph.D., Zhejiang University, Hangzhou.
• 2015.09 - 2019.06, Undergraduate, Computer Science, Zhejiang Univeristy, Hangzhou.
• 2012.09 - 2015.06, The Second Middile School, Huzhou, Zhejiang.

💻 Internships

• 2022.03 - 2023.09, MSRA, Machine Learning Group, Beijing.
• 2021.04 - 2022.03, JD.com, Beijing.
• 2018.06 - 2019.02, YiWise, Hangzhou.