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MixJudge: Learning a Language-Queryable Critic for Vocal Mixing

2026-10-22 06:02:59
Kuan-Hsun Ho, Yuan-Chiao Cheng, Yen-Tung Yeh, Yi-Hsuan Yang
arXiv_CL
   
Abstract

Mixing requires not only applying processing but also assessing the resulting mix. Audio-language models can provide conversa- tional mixing advice, but existing evaluations do not separately test whether they can judge specific mixing issues. Since professional supervision for such judgments is scarce, we construct a curriculum of 11 vocal-mix issues at multiple severity levels and use it to train MixJudge, a language-queryable audio critic. MixJudge shows its ability to retrieve mixing issues, distinguish opposite issues, and order the severity of an issue. Moreover, its judgments transfer to menu selection: given a set of processing candidates, MixJudge often favors versions acoustically closer to a held-out professional version, demonstrating how explicit mixing judgment can support comparison and downstream mixing decisions.

Abstract (translated)

URL

https://arxiv.org/abs/2610.30783

PDF

https://arxiv.org/pdf/2610.30783.pdf

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