activity
20192023
most citedDescription and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

105 citations · 253 across the 10 of their papers we have counts for

collaborators

10 papers

cs.SD2023★ 4 cited

Description and Discussion on DCASE 2023 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Kota Dohi, Keisuke Imoto, Noboru Harada +7

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…

cs.SD2022★ 27 cited

Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques

Kota Dohi, Keisuke Imoto, Noboru Harada +7

We present the task description and discussion on the results of the DCASE 2022 Challenge Task 2: ``Unsupervised anomalous sound detection (ASD) for machine condition monitoring ap…

cs.SD2022★ 22 cited

MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Task

Kota Dohi, Tomoya Nishida, Harsh Purohit +5

We present a machine sound dataset to benchmark domain generalization techniques for anomalous sound detection (ASD). Domain shifts are differences in data distributions that can d…

eess.AS2021★ 34 cited

Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions

Yohei Kawaguchi, Keisuke Imoto, Yuma Koizumi +6

We present the task description and discussion on the results of the DCASE 2021 Challenge Task 2. In 2020, we organized an unsupervised anomalous sound detection (ASD) task, identi…

cs.SD2021★ 1 cited

MIMII DUE: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection with Domain Shifts due to Changes in Operational and Environmental Conditions

Ryo Tanabe, Harsh Purohit, Kota Dohi +4

In this paper, we introduce MIMII DUE, a new dataset for malfunctioning industrial machine investigation and inspection with domain shifts due to changes in operational and environ…

eess.AS2021★ 5 cited

Flow-based Self-supervised Density Estimation for Anomalous Sound Detection

Kota Dohi, Takashi Endo, Harsh Purohit +2

To develop a machine sound monitoring system, a method for detecting anomalous sound is proposed. Exact likelihood estimation using Normalizing Flows is a promising technique for u…