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Toshiko Shibano

Toshiko Shibano has 2 papers in our library, in 2021–2022, most of them on Speech & spoken language, English, Language models & pretraining; often with Peter Sullivan, Muhammad Abdul-Mageed.

2 papers in our library · 2021–2022

OpenAlex · h-index 2 · 2 works · 16 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 5 times in our library · ⭐ Paper Stars ranking: #5704

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 British ColumbiaVancouver · Canada2021–2022 · 2 paperscurrent

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 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 3Research subjects and languages the work is about.English · 2 worksSpeech & spoken language · 2 worksLanguage models & pretraining · 1 work

 Works by year

2020s

20221 paperImproving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding20211 paperSpeech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning

 Papers

The most cited first (OpenAlex and our library).

  1. Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding (2022 · 16 citations)
    ASR systems tuned for native (L1) English perform noticeably worse on non-native (L2) speakers. Accents shift pronunciation, and little annotated accented audio exists for training. The authors start from the self-trained wav2vec 2.0 Large model (Wav2Vec 2.0-ST) and fine-tune it with CTC under many data conditions…
  2. Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning (2021 · 5 citations)
    English speech recognisers do noticeably worse on non-native (L2) speakers. The main causes are first-language pronunciation habits and the small amount of transcribed accented speech. The authors test whether a strong pretrained model can close this gap through modest fine-tuning alone, with no external language…

 Co-authors here

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

 Cited by

Papers of our library cite their works 5 times (of the 141,840 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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