1st Clarity Prediction Challenge (CPC1) dataset for hearing aid speech intelligibility prediction
Contributors
- 1. University of Nottingham
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2.
University of Salford
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3.
Cardiff University
- 4. University of Nottingham School of Medicine
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5.
Federico Santa María Technical University
Description
This dataset was created for the first Clarity Prediction Challenge (CPC1), which investigated the prediction of speech intelligibility for hearing-aid users in noisy acoustic environments. The challenge is now complete, but the dataset is made available for ongoing research. It can be used to develop and evaluate algorithms that estimate speech intelligibility across a range of acoustic and hearing-aid conditions.
The release includes audio signals, listener metadata, and supporting documentation. These materials enable reproducible evaluation of past challenge submissions as well as benchmarking of new approaches.
Further information about the challenge, including background, task definitions, and baseline systems, is available at: https://claritychallenge.org/docs/cpc1/cpc1_intro
Files
Files
(20.7 GB)
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md5:db62ba9c018dca184453fc60901519df
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md5:6d68b89b16d8da8fe54989df8144ec14
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14.2 GB | Download |
Additional details
Related works
- Is described by
- Conference paper: 10.21437/interspeech.2022-10821 (DOI)
Software
- Repository URL
- https://github.com/claritychallenge/clarity
- Programming language
- Python
- Development Status
- Active