Sound event detection in synthetic domestic environments
Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
We present a comparative analysis of the performance of state-of-the-art sound event detection systems. In particular, we study the robustness of the systems to noise and signal degradation, which is known to impact model generalization. Our analysis is based on the results of task 4 of the DCASE 2019 challenge, where submitted systems were evaluated on, in addition to real-world recordings, a series of synthetic soundscapes that allow us to carefully control for different soundscape characteristics. Our results show that while overall systems exhibit significant improvements compared to previous work, they still suffer from biases that could prevent them from generalizing to real-world scenarios.
Recommended citation: @inproceedings{serizel2020sound, title={Sound Event Detection in Synthetic Domestic Environments}, author={Serizel, Romain and Turpault, Nicolas and Shah, Ankit and Salamon, Justin}, booktitle={2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, pages={86--90}, year={2020}, organization={IEEE} }
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