Publications

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

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

Publication date: 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:  Adobe Research iconAI & Machine Learning Adobe Research iconAudio