The First Cadenza Signal Processing Challenge: Improving Music for Those With a Hearing Loss
Gerardo Roa Dabike, Scott Bannister, Jennifer Firth, Simone Graetzer,, Rebecca Vos, Michael A. Akeroyd, Jon Barker, Trevor J. Cox, Bruno Fazenda,, Alinka Greasley, William Whitmer

TL;DR
The Cadenza Signal Processing Challenge aims to develop innovative audio processing techniques to enhance music listening experiences for individuals with hearing loss, focusing on scenarios like headphone listening and car environments.
Contribution
This paper introduces a novel challenge framework for improving music quality for hearing-impaired listeners through signal processing tasks like source separation and noise reduction.
Findings
Development of personalized remixing techniques
Enhanced audio quality in noisy environments
Objective and subjective evaluation methods established
Abstract
The Cadenza project aims to improve the audio quality of music for those who have a hearing loss. This is being done through a series of signal processing challenges, to foster better and more inclusive technologies. In the first round, two common listening scenarios are considered: listening to music over headphones, and with a hearing aid in a car. The first scenario is cast as a demixing-remixing problem, where the music is decomposed into vocals, bass, drums and other components. These can then be intelligently remixed in a personalized way, to increase the audio quality for a person who has a hearing loss. In the second scenario, music is coming from car loudspeakers, and the music has to be enhanced to overcome the masking effect of the car noise. This is done by taking into account the music, the hearing ability of the listener, the hearing aid and the speed of the car. The audio…
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Taxonomy
TopicsHearing Loss and Rehabilitation · Noise Effects and Management · Speech and Audio Processing
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
