Clarity: Machine Learning Challenges to Revolutionise Hearing Device Processing
Abstract
In the Clarity project, we will run a series of machine learning challenges to revolutionise speech processing for hearing devices. Over five years, there will be three paired challenges. Each pair will consist of a competition focussed on hearing-device processing ("enhancement") and another focussed on speech perception modelling ("prediction"). The enhancement challenges will deliver new and improved approaches for hearing device signal processing for speech. The parallel prediction challenges will develop and improve methods for predicting speech intelligibility and quality for hearing impaired listeners. This Engineering and Physical Sciences Research Council (EPSRC) funded project involves researchers from the Universities of Sheffield, Salford, Nottingham and Cardiff in conjunction with the Hearing Industry Research Consortium, Action on Hearing Loss, Amazon, and Honda. To register interest in the challenges, go to www.claritychallenge.org.
Keywords
Cite
@article{arxiv.2006.11140,
title = {Clarity: Machine Learning Challenges to Revolutionise Hearing Device Processing},
author = {Simone Graetzer and Michael Akeroyd and Jon P. Barker and Trevor J. Cox and John F. Culling and Graham Naylor and Eszter Porter and Rhoddy Viveros Muñoz},
journal= {arXiv preprint arXiv:2006.11140},
year = {2020}
}
Comments
3 pages, 2 figures