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This paper introduces our system submission for the Cadenza ICASSP 2024 GrandChallenge, which presents the problem of remixing and enhancing music forhearing aid users. Our system placed first in the challenge, achieving the bestaverage Hearing-Aid Audio Quality Index (HAAQI) score on the evaluation dataset. We describe the system, which uses an ensemble of deep learning musicsource separators that are fine tuned on the challenge data. We demonstrate theeffectiveness of our system through the challenge results and analyze theimportance of different system aspects through ablation studies.

Remixing Music for Hearing Aids Using Ensemble of Fine-Tuned Source Separators