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Sanyuan Chen

Sanyuan Chen has 2 papers in our library, in 2023–2025, most of them on Speech & spoken language, Language models & pretraining, Efficient models & compression; often with Jinyu Li, Long Zhou, Sheng Zhao.

2 papers in our library · 2023–2025

OpenAlex · ORCID · Wikidata · h-index 17 · 42 works · 3,160 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 327 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4572

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢MicrosoftRedmond · United States2020–2024 · 16 papers🎓Harbin Institute of TechnologyHarbin · China2020–2025 · 11 papers🏢Microsoft Research AsiaBeijing · China2022–2024 · 3 papers🏛️Chinese Academy of SciencesBeijing · China2012–2013 · 3 papers🔬Institute of SemiconductorsBeijing · China2012–2013 · 3 papers🔬State Key Laboratory on Integrated OptoelectronicsBeijing · China2012–2013 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksMedicine · 1 workArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksSignal Processing · 2 worksPhysiology · 1 workPsychology · 1 workExperimental and Cognitive Psychology · 1 work

🧭 Topics 3Research subjects and languages the work is about.Speech & spoken language · 2 worksLanguage models & pretraining · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers (2023 · 335 citations)
    Zero-shot text-to-speech means reproducing a voice the system never saw during training. Earlier approaches relied on speaker adaptation or dedicated speaker encoders. Models trained on small, studio-clean corpora tend to generalize poorly to new speakers.
  2. Autoregressive Speech Synthesis without Vector Quantization (2025 · 25 citations)
    Codec-based zero-shot TTS systems such as VALL-E represent speech as vector-quantized tokens. These tokens lose fidelity compared with continuous features. Sampling from them can also produce silences or noise loops, and the systems need a two-pass AR+NAR decoder. MELLE removes quantization entirely: a single…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Neural Codec Language Models are Zero-Shot Text to Speech SynthesizersarXiv:2301.02111Chengyi Wang, Sanyuan Chen, Yu Wu, et al.2023 · 335 citations
  2. Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetSanyuan Chen et al.2020 · 257 citations
  3. WavLLM: Towards Robust and Adaptive Speech Large Language Model ↗Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yetShujie Hu et al.2024 · 98 citations
  4. Autoregressive Speech Synthesis without Vector QuantizationAnnual Meeting of the Association for Computational Linguistics (ACL)Lingwei Meng, Long Zhou, Shujie Liu, et al.2025 · 25 citations

 Co-authors here

12 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 327 times (of the 149,439 papers whose bibliographies we read); 61 citing papers with a page here →.

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