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Dutch Open Speech Recognition Benchmark

Results of Dutch ASR models, collected by the community

Dutch Open Speech Recognition Benchmark

Welcome to the Dutch Open Speech Recognition Benchmark website! We encourage contributions from all researchers and developers working with Dutch Automatic Speech Recognition.

OH-SMArt Project Benchmark

The following results were achieved during the PDI-SSH Oral History - Stories at the Museum around Art (OH-SMArt) project (2022-2025) and are reported by University of Twente:

Broadcast News and Telephone Conversations (N-Best) Benchmark

Underrepresented Speakers (JASMIN-CGN) Benchmark

Common Voice (CV) Benchmark

Pathological Speech (COPAS) Benchmark*

*These results were obtained during and after the project, in preparation for Interspeech 2025.

Environment setup for benchmarks above

Why do the results differ between whisper-timestamped and faster-whisper?

Medical Speech (HoMed) Benchmark

The following results were achieved during the PDI-SSH Homo Medicinalis (HoMed) project (2021-2024) and are reported by Radboud University:

Results

Environment setup

NISV’s Whisper Benchmark

NISV = Netherlands Institute for Sound & Vision (NL: Nederlands Instituut voor Beeld & Geluid)

The following results were achieved during the same (OH-SMArt) project mentioned above and are reported by University of Twente in collaboration with NISV:

Results for Broadcast News Speech

Results for Conversational Telephone Speech

Data selection for ASR adaptation

The following results were achieved as part of a Ph.D study, funded by the first phase of the HOSAN project (2025) and the MediSpeech project (2025-2028), and are reported by University of Twente:

Results

Contributions

Feel free to click the link at the top that leads you to the GitHub repository of this website. You may add changes if you want by forking the repository, making changes on your fork, then opening a pull request on the source repository.