论文标题
DCASE2020挑战的描述和讨论任务2：无监督的机器状况监控的异常声音检测
Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
论文作者
论文摘要
在本文中，我们介绍任务说明并讨论DCASE 2020挑战任务的结果2：用于机器状况监视的无异常声音的无监督检测。异常声音检测的目的（ASD）是确定从目标机器发出的声音是正常的还是异常的。该任务的主要挑战是在仅提供正常声音样本作为训练数据的情况下检测未知的异常声音。我们将这一挑战设计为ASD研究的第一个基准，其中包括大规模数据集，评估指标和简单的基线系统。我们收到了40支球队的117份意见书，并且由于这一挑战而开发了几种新颖的方法。根据评估结果的分析，我们讨论了两种新方法及其问题。
In this paper, we present the task description and discuss the results of the DCASE 2020 Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition Monitoring. The goal of anomalous sound detection (ASD) is to identify whether the sound emitted from a target machine is normal or anomalous. The main challenge of this task is to detect unknown anomalous sounds under the condition that only normal sound samples have been provided as training data. We have designed this challenge as the first benchmark of ASD research, which includes a large-scale dataset, evaluation metrics, and a simple baseline system. We received 117 submissions from 40 teams, and several novel approaches have been developed as a result of this challenge. On the basis of the analysis of the evaluation results, we discuss two new approaches and their problems.
