Enforcing equal CNN hidden activations for parallel recordings from different microphones improves target-device accuracy in acoustic scene classification and beats MMD-based domain adaptation in these experiments.
Detection and Classification of Acoustic Scenes and Events 2019 25–26 October 2019, New York, NY , USA
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Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification
Enforcing equal CNN hidden activations for parallel recordings from different microphones improves target-device accuracy in acoustic scene classification and beats MMD-based domain adaptation in these experiments.