We present the task description of the Detection and Classification of
Acoustic Scenes and Events (DCASE) 2023 Challenge Task 2: "First-shot
unsupervised anomalous sound detection (ASD) for machine condition monitoring".
The main goal is to enable rapid deployment of ASD systems for new kinds of
machines using only a few normal samples, without the need for hyperparameter
tuning. In the past ASD tasks, developed methods tuned hyperparameters for each
machine type, as the development and evaluation datasets had the same machine
types. However, collecting normal and anomalous data as the development dataset
can be infeasible in practice. In 2023 Task 2, we focus on solving first-shot
problem, which is the challenge of training a model on a few machines of a
completely novel machine type. Specifically, (i) each machine type has only one
section, and (ii) machine types in the development and evaluation datasets are
completely different. We will add challenge results and analysis of the
submissions after the challenge submission deadline.

本文介绍了 DCASE 2023 Challenge Task 2 的任务描述：“适用于机器状态监测的无监督异声检测” 以及采用了仅有一些正常样本的新机器的第一次尝试该问题的解决方案。