Description and Discussion on DCASE 2026 Challenge Task 2: Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
2026-06-01 • Sound
Sound
AI summaryⓘ
The authors describe a challenge called DCASE 2026 Task 2, which focuses on detecting unusual sounds from machines to monitor their condition without using examples of faulty sounds for training. They highlight the common problem that background noise makes it hard to detect these unusual sounds reliably. To improve this, the challenge provides two audio recordings taken near and far from the machine, so participants can better separate machine sounds from noise. The paper also mentions that results and analyses will be shared after the challenge ends.
Anomalous sound detectionMachine condition monitoringUnsupervised learningEnvironmental noiseTwo-channel audioNoise robustnessDCASE challengeAudio signal processing
Authors
Tomoya Nishida, Noboru Harada, Daiki Takeuchi, Daisuke Niizumi, Keisuke Imoto, Kota Dohi, Harsh Purohit, Takashi Endo, Yohei Kawaguchi
Abstract
This paper presents an overview of DCASE 2026 Challenge Task 2, titled "Noise-aware unsupervised anomalous sound detection (UASD) for machine condition monitoring." The task aims to advance noise-robust anomalous sound detection for machine condition monitoring under the unsupervised setting, where only normal machine sounds are available for training. Reliable detection under noisy conditions is crucial for practical deployment, but previous DCASE Task 2 settings provided limited information about environmental noise, potentially limiting UASD performance in highly noisy situations. To address this limitation, DCASE 2026 allows participants to exploit two-channel audio samples simultaneously captured at locations near and far from the target machine. Since the distant microphone is expected to contain relatively stronger environmental noise and weaker direct machine sounds, it may help distinguish environmental noise components from the target machine sounds. After the challenge submission deadline, challenge results and an analysis of the submitted systems will be added.