This dataset contains the baselines submission audio signals for the ICASSP24 challenge. The signals correspond to 10-second consecutive segments of the MUSDB18-HQ test split. The signals were processed according the ICASSP24 requirements. Please refer to the Cadenza challenge website and to the paper for details. Description of files: submission_T001.zip: package containing the audio signals of Baseline 1 submission_T002.zip: package containing the audio signals of Baseline 2 gains.json: Json file with all posible gain combinations. head_loudspeaker_positions.json: Json file with the different combination of head rotations listeners.test.json: Json file with the listeners audiograms scenes.test.json: Json file with the scenes descriptions scene_listeners.test.json: Json file with the list of listeners to process per scene musdb18.test.json: Json file with the description of the MUSDB18-HQ test split HAAQI_scores.zip: ZIP file containing one CSV per Team with HAAQI scores The audio signals are organised as: enhanced_signals/scene___remix.flac where: Scene_ID: is the unique id to identify each scene. Listener_ID: 53 unique ids to identify each listener.

Cadenza This is the baseline submission data for the ICASSP 2024 Cadenza Grand Challenge (ICASSP24). The Cadenza Challenges are improving music production and processing for people with a hearing loss. According to The World Health Organization, 430 million people worldwide have a disabling hearing loss. Studies show that not being able to understand lyrics is an important problem to tackle for those with hearing loss. Consequently, this task is about improving the intelligibility of lyrics when listening to pop/rock over headphones. But this needs to be done without losing too much audio quality - you can't improve intelligibility just by turning off the rest of the band! We will be using one metric for intelligibility and another metric for audio quality, and giving you different targets to explore the balance between these metrics. Please see the Cadenza website for a full description of the data

This repository only includes the submission samples for both baselines. If you need access to the submission samples for all submissions, please contact us at cadenzachallengecontact@gmail.com. All submissions description: 19 packages (including baselines) A total size of 384 GB (including baselines) 19,200 signals per team

Cite as: G. Roa-Dabike, M. A. Akeroyd, S. Bannister, J. P. Barker, T. J. Cox, B. Fazenda, J. Firth, S. Graetzer, A. Greasley, R. R. Vos and W. M. Whitmer, "The First Cadenza Challenges: Using Machine Learning Competitions to Improve Music for Listeners With a Hearing Loss," in IEEE Open Journal of Signal Processing.