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Yiwei Gu

Yiwei Gu has 2 papers in our library, in 2018–2022, most of them on English, Speech & spoken language; often with Yang Liu, Bin Wang, Hui Lin.

2 papers in our library · 2018–2022

OpenAlex · ORCID · h-index 6 · 22 works · 198 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 2 times in our library · ⭐ Paper Stars ranking: #10461

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

🎓University of Southern CaliforniaLos Angeles · United States2025–2026 · 4 paperscurrent🎓Fudan UniversityShanghai · China2016–2018 · 5 papers🎓University of KentuckyLexington · United States2023–2025 · 3 papers🏥Markey Cancer CenterLexington-Fayette · United States2025 · 2 papers🏥Nanfang HospitalGuangzhou · China2025 · 2 papers🎓Southern Medical UniversityGuangzhou · China2025 · 2 papers🎓East China Normal UniversityShanghai · China2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksPsychology · 2 worksArtificial Intelligence · 2 worksExperimental and Cognitive Psychology · 2 worksLanguage and Linguistics · 2 worksSignal Processing · 2 works

🧭 Topics 2Research subjects and languages the work is about.English · 2 worksSpeech & spoken language · 1 work

 Works by year

2020s

20221 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Automatically Detecting Reduced-formed English Pronunciations by Using Deep Learning (2022 · 4 citations)
    The paper addresses automatic detection of reduced-form pronunciations in the speech of Chinese learners of English.
  2. Attention-based sequence-to-sequence model for speech recognition: development of state-of-the-art system on LibriSpeech and its application to non-native English (2018 · 2 citations)
    The authors ask whether an end-to-end attention model can match or beat classic hybrid HMM/NN recognizers, especially for English spoken by learners.

 Co-authors here

4 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 2 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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