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Speech Technology Papers·2026
Icon for item

Learning Where to Split: Dynamic Band Splitting for Audio Source Separation

Bingzhe Zhang, Kai Li +1·Department of Computer Science and Technology, Institute for AI, BNRist, Tsinghua University, Beijing 100084, China, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China +1

Adapts frequency-band boundaries to each audio mixture under a fixed band-token budget to improve source separation. Predicts content-conditioned boundary scores, selects bands with hard Top-K, pools variable-width bands into tokens, and decodes full-resolution complex masks—showing large SI-SDR gains on DnR v2, MUSDB18-HQ and EchoSet.

#audio#speech#paper#research#code+2
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