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Preprint Aug 2026

Anomalous Sound Detection Meets Noise-Aware Self-Supervised Learning

In this paper, we introduce noise-aware self-supervised learning (NA-SSL) models for noise-aware anomalous sound detection (NA-ASD). NA-ASD is an ASD task with two-channel audio recordings, where one microphone is located close to the target machine and the other is located farther away to capture noise. For this task,...

Takuya Fujimura, G. Wichern, Yoshiki Masuyama et al. · 0 citations

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