Improving Sound Event Detection Metrics: Insights from DCASE 2020 - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2021

Improving Sound Event Detection Metrics: Insights from DCASE 2020

Résumé

The ranking of sound event detection (SED) systems may be biased by assumptions inherent to evaluation criteria and to the choice of an operating point. This paper compares conventional event-based and segment-based criteria against the Polyphonic Sound Detection Score (PSDS)'s intersection-based criterion, over a selection of systems from DCASE 2020 Challenge Task 4. It shows that, by relying on collars , the conventional event-based criterion introduces different strictness levels depending on the length of the sound events, and that the segment-based criterion may lack precision and be application dependent. Alternatively, PSDS's intersection-based criterion overcomes the dependency of the evaluation on sound event duration and provides robustness to labelling subjectivity, by allowing valid detections of interrupted events. Furthermore, PSDS enhances the comparison of SED systems by measuring sound event modelling performance independently from the systems' operating points.
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Dates et versions

hal-02978422 , version 1 (26-10-2020)

Identifiants

Citer

Giacomo Ferroni, Nicolas Turpault, Juan Azcarreta, Francesco Tuveri, Romain Serizel, et al.. Improving Sound Event Detection Metrics: Insights from DCASE 2020. ICASSP 2021 - 46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto/Virtual, Canada. ⟨10.1109/ICASSP39728.2021.9414711⟩. ⟨hal-02978422⟩
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