The Clarity & Cadenza Challenges

Akeroyd, M.; Bailey, W.; Bannister, S.; Firth, J.; Graetzer, S.; Roa Dabike, G.; Tu, Z.; Vos, R.; Research Project, C.; Research Project, C.

Abstract

Clarity (Speech in noise) and Cadenza (music) are two EPSRC projects that are exploiting the latest in machine learning to create improved listening experiences for those with a hearing loss. In both we are running a series of open competitions, for which entrants are challenged to improve and personalise the audio for listeners with a hearing loss. This challenge methodology fosters a new research community devoted to making music and speech more accessible, as well as creating open-source tools and databases to facilitate future investigations. The challenges pose a variety of dilemmas to the competitors: for instance, while a hearing aid must manipulate live speech with low latency and limited computing power, recorded music from consumer devices can be pre-processed with non-causal techniques using cloud computing. In this presentation we will update the latest news on the third Clarity challenge and the first Cadenza challenge and report on all the open-access computational tools and rating scales we have developed.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th Convention of the European Acoustics Association Forum Acusticum 2023
• Acceptance Date: Aug 7, 2023
• Online Publication Date: Jan 17, 2024
• Deposit Date: Feb 21, 2024
• Publicly Available Date: Feb 21, 2024
• Journal: Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023
• Peer Reviewed: Peer Reviewed
• Pages: 1209-1211
• DOI: https://doi.org/10.61782/fa.2023.0876