--- title: "Yaqian Zhou — author profile and papers" description: "Yaqian Zhou, Fudan University: 2 papers on Elamur Research (2023), h-index 15 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/yaqian-zhou/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yaqian-zhou/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yaqian Zhou # Yaqian Zhou Yaqian Zhou has 2 papers in our library, in 2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/), [Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/); often with [Dong Zhang](https://md.research.elamur.ai/free/en/authors/dong-zhang/), [Shimin Li](https://md.research.elamur.ai/free/en/authors/shimin-li/), [Xin Zhang](https://md.research.elamur.ai/free/en/authors/xin-zhang/). 2 papers in our library · 2023 [OpenAlex](https://openalex.org/A5100559702) · [**h-index 15**](https://openalex.org/authors/A5100559702) · [67 works](https://openalex.org/works?filter=author.id:A5100559702) · [895 citations](https://openalex.org/works?filter=author.id:A5100559702&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yaqian-zhou/#papers) · [🔗 265 citations in our library](https://md.research.elamur.ai/free/en/authors/yaqian-zhou/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Star rank #3244](https://md.research.elamur.ai/free/en/paper-stars/page/33/#star-3244) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yaqian+Zhou) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yaqian+Zhou) · [dblp](https://dblp.org/search?q=Yaqian+Zhou) · [ACL Anthology](https://aclanthology.org/search/?q=Yaqian+Zhou) ## Affiliations [🎓**Fudan University** Shanghai · China 2003–2025 · 40 papers*current*](https://md.research.elamur.ai/free/en/universities/fudan-university/) · [🎓**University of Science and Technology Beijing** Beijing · China 2022–2023 · 3 papers](https://ror.org/02egmk993) · [🎓**Wuhan University of Technology** Wuhan · China 2020–2023 · 2 papers](https://ror.org/03fe7t173) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed. ## Topics [Language models & pretraining (2)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Dialogue systems (1)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Speech & spoken language (1)](https://md.research.elamur.ai/free/en/topics/speech/) · [Tokenization & segmentation (1)](https://md.research.elamur.ai/free/en/topics/tokenization/) ## Works by year ### 2020s [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/yaqian-zhou/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechgpt-empowering-large-language-models/)** *(2023 · 346 citations)* Most systems that let large language models talk chain separate ASR and TTS modules around a text LLM. This design keeps the LLM's knowledge from reaching the speech modality, discards cues such as emotion and prosody, and lets errors pile up between stages. SpeechGPT addresses this by converting speech into discrete… 2. **[SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechtokenizer-unified-speech-tokenizer-speech/)** *(2023 · 51 citations)* Speech large language models rely on discrete tokens of two kinds. Semantic tokens, such as k-means units from HuBERT, follow linguistic content but discard voice traits. Acoustic tokens from neural codecs like EnCodec retain audio detail but correspond poorly to text. The authors first build SLMTokBench, a benchmark… ## Also in our library 1 more work of theirs is in our library without a page here yet; it will appear as we publish them. ## Co-authors here 5 co-authors with a page, the most papers together first. - [Dong Zhang](https://md.research.elamur.ai/free/en/authors/dong-zhang/) ×2 - [Shimin Li](https://md.research.elamur.ai/free/en/authors/shimin-li/) ×2 - [Xin Zhang](https://md.research.elamur.ai/free/en/authors/xin-zhang/) ×2 - [Xipeng Qiu](https://md.research.elamur.ai/free/en/authors/xipeng-qiu/) ×2 - [Jun Zhan](https://md.research.elamur.ai/free/en/authors/jun-zhan/) ## Cited by Papers of our library cite their works 265 times (of the 140,884 papers whose bibliographies we read); [13 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yaqian-zhou/cited-by/).