Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2021

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

Résumé

We propose a benchmark of state-of-the-art sound event detection systems (SED). We designed synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2021 task 4 depending on time related modifications (time position of an event and length of clips) and we study the impact of non-target sound events and reverberation. We show that the localization in time of sound events is still a problem for SED systems. We also show that reverberation and non-target sound events are severely degrading the performance of the SED systems. In the latter case, sound separation seems like a promising solution.
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Dates et versions

hal-02984675 , version 1 (31-10-2020)

Identifiants

Citer

Nicolas Turpault, Romain Serizel, Scott Wisdom, Hakan Erdogan, John R Hershey, et al.. Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes. ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto/Virtual, Canada. ⟨10.1109/ICASSP39728.2021.9414789⟩. ⟨hal-02984675⟩
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