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

摘要

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.