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In this paper, we present the task description and discuss the results of theDCASE 2020 Challenge Task 2: Unsupervised Detection of Anomalous Sounds forMachine Condition Monitoring. The goal of anomalous sound detection (ASD) is toidentify whether the sound emitted from a target machine is normal oranomalous. The main challenge of this task is to detect unknown anomaloussounds under the condition that only normal sound samples have been provided astraining data. We have designed this challenge as the first benchmark of ASDresearch, which includes a large-scale dataset, evaluation metrics, and asimple baseline system. We received 117 submissions from 40 teams, and severalnovel approaches have been developed as a result of this challenge. On thebasis of the analysis of the evaluation results, we discuss two new approachesand their problems.

Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring