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Yun Hao

Yun Hao has 2 papers in our library, in 2025–2026, most of them on Speech & spoken language, Low-resource languages, Language models & pretraining; often with Martijn Wieling, Reihaneh Amooie, Wietse de Vries.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 2 · 11 works · 13 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #12321

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 Yang Ming Chiao Tung UniversityHsinchu · Taiwan2024–2026 · 7 paperscurrent🎓National Cheng Kung UniversityTainan · Taiwan2026 · 1 papercurrent🎓University of GroningenGroningen · Netherlands2025 · 2 papers

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

 Fields, topics and concepts

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSignal Processing · 2 works

🧭 Topics 5Research subjects and languages the work is about.Low-resource languages · 2 worksSpeech & spoken language · 2 worksEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Can Large Language Models Reliably Correct Errors in Low-Resource ASR? A Contamination-Aware Case Study on West Frisian (2026)
    The paper asks whether LLMs can fix the output of a speech recognizer for West Frisian, a language with about 400,000 speakers and little training data.
  2. Evaluating Standard and Dialectal Frisian ASR: Multilingual Fine-tuning and Language Identification for Improved Low-resource Performance (2025)
    The paper asks how to build better speech recognition for Frisian, a low-resource minority language of the Netherlands, and how well such systems handle its regional dialects (Clay, Wood and South Frisian).

 Co-authors here

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

Updated

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