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Sound Event Detection in Synthetic Domestic Environments

机译:综合家庭环境中的声音事件检测

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We present a comparative analysis of the performance of state-of-the-art sound event detection systems. In particular, we study the robustness of the systems to noise and signal degradation, which is known to impact model generalization. Our analysis is based on the results of task 4 of the DCASE 2019 challenge, where submitted systems were evaluated on, in addition to real-world recordings, a series of synthetic soundscapes that allow us to carefully control for different soundscape characteristics. Our results show that while overall systems exhibit significant improvements compared to previous work, they still suffer from biases that could prevent them from generalizing to real-world scenarios.
机译:我们对最先进的声音事件检测系统的性能进行了比较分析。特别是,我们研究了系统对噪声和信号降级的鲁棒性,已知该鲁棒性会影响模型的概括。我们的分析基于DCASE 2019挑战任务4的结果,除了真实世界的录音之外,还对提交的系统进行了评估,此外还对一系列合成音景进行了评估,这些音景使我们能够仔细控制不同的音景特性。我们的结果表明,尽管与以前的工作相比,整个系统显示出显着的改进,但它们仍然存在偏见,可能会阻止它们推广到实际情况。

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