The 2nd Clarity Prediction Challenge: A machine learning challenge for hearing aid intelligibility prediction

Barker, Jon, Akeroyd, Michael A., Bailey, Will, Cox, Trevor J., Culling, John F. ORCID: https://orcid.org/0000-0003-1107-9802, Firth, Jennifer, Graetzer, Simone and Naylor, Graham 2024. The 2nd Clarity Prediction Challenge: A machine learning challenge for hearing aid intelligibility prediction. Presented at: 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Republic of Korea, 14-19 April 2024. Proceedings ICASSP 2024 - International Conference on Acoustics, Speech and Signal Processing. IEEE, pp. 11551-11555. 10.1109/ICASSP48485.2024.10446441

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Abstract

This paper reports on the design and outcomes of the 2nd Clarity Prediction Challenge (CPC2) for predicting the intelligibility of hearing aid processed signals heard by individuals with a hearing impairment. The challenge was designed to promote new approaches for estimating the intelligibility of hearing aid signals that can be used in future hearing aid algorithm development. It extends an earlier round (CPC1, 2022) in a number of critical directions, including a larger dataset coming from new speech intelligibility listening experiments, a greater degree of variability in the test materials, and a design that requires prediction systems to generalise to unseen algorithms and listeners. This paper provides a full description of the new publicly available CPC2 dataset, the CPC2 challenge design, and the baseline systems. The challenge attracted 12 systems from 9 research teams. The systems are reviewed, their performance is analysed and conclusions are presented, with reference to the progress made since the earlier CPC1 challenge. In particular, it is seen how reference-free, non-intrusive systems based on pre-trained large acoustic models can perform well in this context.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Psychology
Publisher:	IEEE
ISBN:	979-8-3503-4485-1
Date of First Compliant Deposit:	26 March 2024
Date of Acceptance:	18 March 2024
Last Modified:	11 Jun 2024 09:40
URI:	https://orca.cardiff.ac.uk/id/eprint/167561

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