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cs.SD2026
Improving Text-to-Music Generation with Human Preference Rewards
Yonghyun Kim, Junwon Lee, Haiwen Xia +2
We describe our entry to the efficiency track of the Academic Text-to-Music (ATTM) Grand Challenge at ICME 2026. Beyond the challenge protocol's FAD-CLAP and CLAP score, we add a l…
cs.SD2026
TuneJury: An Open Metric for Improving Music Generation Preference Alignment
Yonghyun Kim, Junwon Lee, Haiwen Xia +5
We introduce TuneJury, an open, instance-level pairwise reward model for text-to-music that predicts a music preference score from a text prompt and an audio clip. The released che…
cs.SD2026
UNMIXX: Untangling Highly Correlated Singing Voices Mixtures
Jihoo Jung, Ji-Hoon Kim, Doyeop Kwak +3
We introduce UNMIXX, a novel framework for multiple singing voices separation (MSVS). While related to speech separation, MSVS faces unique challenges: data scarcity and the highly…