Zheng-Hua Tan

You can ditch mean pooling: adaptive temporal pooling strategies for pre-trained audio embeddings dramatically improve training-free anomaly detection, even beating fully trained models.

Blindly applying anomalous sound detection models trained with machine-specific data can lead to significant performance drops when the machine identity is unknown at test time, highlighting a critical gap in current ASD benchmarks.