A Multi-Branch Hierarchy-Aware Framework for Heterogeneous Audio Classification
This technical report describes our system for Task 1 of the DCASE 2026 Challenge, which aims to classify heterogeneous audio recordings according to the Broad Sound Taxonomy (BST). The task requires both accurate second-level prediction and consistency with the top-level taxonomy. Our system is built on CLAP-based audio-text representations and is improved along three strategies: expanding the training set with a filtered subset of BSD35k, enhancing acoustic modeling with feature-specific branches, and refining predictions using hierarchy-aware classifiers and KNN-based post-processing. Among the acoustic features considered, the log-STFT branch provides the strongest single-model perfor...
| Authors | Beile Ning, Jiayi Yu, Zitong Wang et al. |
|---|---|
| Primary category | cs.SD |
| Published | 2 July 2026 |
| Last updated at source | 2 July 2026 |
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