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About this paper
Jinjie Shi, Wei Hua, Kunzhu Xie, Make Li, Yuchen Liu, Joshua Reiss
An analysis of automatic mixing as a sequence of local and global tasks shows that functional track grouping can improve downstream mix quality. Across controlled listening experiments on three multitrack pop and rock excerpts, two-stage versions of MEGAMI and Diff-MST received higher ratings than their single-stage counterparts, while MEGAMI benefited particularly from a seven-group, mixing-oriented organization.
Key insights
- Full-mix capability does not transfer uniformly to local mixing: MEGAMI performed relatively well on intra-group tasks, whereas Diff-MST performed substantially worse than both MEGAMI and the rule-based ELL method.
- Functional grouping mattered more consistently than intra-group loudness balancing. MEGAMI improved with seven mixing-oriented groups, while Diff-MST degraded under instrument-based grouping.
- The results support treating grouping and local balance as explicit design stages, with a learned model coordinating relationships between the resulting group stems.
Summary by alphaXiv.
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