Acoustic Scene Classification
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Related Articles from SNS
Towards Event-Robust Acoustic Scene Classification
arXiv:2606.06921v1 Announce Type: new Abstract: This paper introduces the Event-Shifted Acoustic Scene (ESAS) dataset, a novel benchmark for evaluating the robustness of Acoustic Scene Classification (ASC) systems against unknown sound events. Existing ASC datasets typically contain recordings of clean and consistent audio, while real-world environments often include diverse and unexpected sound events. To bridge this gap, ESAS simulates real-world acoustic variability by injecting...
Drift-Augmented Scoring: Text-Derived Noise Robustness for Zero-Shot Audio-Language Classification
arXiv:2606.04844v1 Announce Type: new Abstract: Contrastive audio-language models such as CLAP enable zero-shot audio classification: a sound is labelled by matching its embedding to text prompt embeddings, with no labelled audio. This matching breaks down under acoustic noise, where accuracy and mAP fall by 12-30 percentage points at 0 dB SNR on standard benchmarks. We propose Drift Augmented Scoring (DAS), a small per-class bonus added to the cosine score.