论文标题
改进声音事件检测指标：Dcase 2020的见解
Improving Sound Event Detection Metrics: Insights from DCASE 2020
论文作者
论文摘要
声音事件检测（SED）系统的排名可能会因评估标准固有的假设和操作点的选择而有偏见。本文将基于事件和细分市场的常规标准与多形声音检测得分（PSD）的基于相交的标准进行了比较，而在DCASE 2020挑战任务4中选择了一系列系统。它表明，依靠基于事件的标准，基于事件的标准依靠基于sect efferition的crection和crection的长度不足。另外，PSD的基于相交的标准克服了评估对声音事件持续时间的依赖性，并通过允许对中断事件的有效检测来为标记主观性提供鲁棒性。此外，PSD通过独立于系统的操作点来测量声音事件建模性能来增强SED系统的比较。
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.
