Sound Event Detection and Separation: A Benchmark on DESED Synthetic Soundscapes

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Published June 8, 2021

Nicolas Turpault, Romain Serizel, Scott Wisdom, Hakan Erdogan, John R. Hershey, Eduardo Fonseca, Prem Seetharaman, Justin Salamon

We propose a benchmark of state-of-the-art sound event detection systems (SED). We design synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2020 Task 4 as a function of time-related modifications (time position of an event and length of clips) and study the impact of non-target sound events and reverberation. We show that temporal localization of sound events remains a challenge for SED systems. We also show that reverberation and non-target sound events severely degrade system performance. In the latter case, sound separation seems like a promising solution.

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Research Areas:  AI & Machine Learning Audio