论文标题
使用声音分离改善家庭环境中的声音事件检测
Improving Sound Event Detection In Domestic Environments Using Sound Separation
论文作者
论文摘要
在现实世界录音上执行声音事件检测通常意味着要处理重叠的目标声音事件和非目标声音，也称为干扰或噪声。到目前为止，这些问题主要在分类器级别解决。我们建议将声音分离作为声音事件检测的预处理。在本文中，我们从在免费的通用声音分离数据集和Dcase 2020 Task 4声音事件检测基线的声音分离模型开始。我们探索不同的方法，将分离的声源和原始混合物组合在声音事件检测中。此外，我们研究了将声音分离模型适应声音事件检测数据对声音分离和声音事件检测的影响。
Performing sound event detection on real-world recordings often implies dealing with overlapping target sound events and non-target sounds, also referred to as interference or noise. Until now these problems were mainly tackled at the classifier level. We propose to use sound separation as a pre-processing for sound event detection. In this paper we start from a sound separation model trained on the Free Universal Sound Separation dataset and the DCASE 2020 task 4 sound event detection baseline. We explore different methods to combine separated sound sources and the original mixture within the sound event detection. Furthermore, we investigate the impact of adapting the sound separation model to the sound event detection data on both the sound separation and the sound event detection.
