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Fu-An Chao

Fu-An Chao has 2 papers in our library, in 2021–2026, most of them on Language models & pretraining, Vision & language, English; often with Berlin Chen, Bi-Cheng Yan.

2 papers in our library · 2021–2026

OpenAlex · h-index 8 · 33 works · 144 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 2 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5712

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

🎓National Taiwan Normal UniversityTaipei · Taiwan2019–2026 · 16 paperscurrent🎓National Chengchi UniversityTaipei · Taiwan2009–2019 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksPsychology · 1 workArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksExperimental and Cognitive Psychology · 1 workSignal Processing · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.English · 1 workLanguage models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20261 paperMASA: A Novel Multimodal Foundation Model for L2 Speaking Assessment in Picture-description Scenarios20211 paperTowards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods

 Papers

The most cited first (OpenAlex and our library).

  1. Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods (2021 · 20 citations)
    Computer-assisted pronunciation training needs mispronunciation detection and diagnosis (MDD) that works for learners of English with many different native-language accents.
  2. MASA: A Novel Multimodal Foundation Model for L2 Speaking Assessment in Picture-description Scenarios (2026)
    MASA is a scoring model for automatic speaking assessment (ASA) of second-language (L2) learners in picture-description tasks.

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. Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating MethodsIEEE Automatic Speech Recognition and Understanding Workshop (ASRU)Shao-Wei Fan Jiang, Bi-Cheng Yan, Tien-Hong Lo, et al.2021 · 20 citations
  2. MASA: A Novel Multimodal Foundation Model for L2 Speaking Assessment in Picture-description ScenariosLanguage Resources and Evaluation Conference (LREC)Bi-Cheng Yan, Fu-An Chao, Hong-Yun H.Y. Lin, et al.2026
  3. RABIT: Rationale-Based Distillation Towards Interpretable Automatic Speaking Assessment via a Small Language ModelProceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026) · original ↗ · no summary yetBi-Cheng Yan et al.2026
  4. Probing the Hidden Talent of ASR Foundation Models for L2 English Oral AssessmentarXiv:2510.16387 · original ↗ · no summary yetFu-An Chao, Bi-Cheng Yan, Berlin Chen2025

 Co-authors here

2 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 141,840 papers whose bibliographies we read).

Updated

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