activity
20192021
most citedDescription and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

105 citations · 157 across the 5 of their papers we have counts for

collaborators

7 papers

eess.AS202134 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

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.AS20215 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…

eess.AS202013 cited

Deep Autoencoding GMM-based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-parameter Optimization

Harsh Purohit, Ryo Tanabe, Takashi Endo +3

Failures or breakdowns in factory machinery can be costly to companies, so there is an increasing demand for automatic machine inspection. Existing approaches to acoustic signal-ba…

eess.AS2020105 cited

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

Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto +8

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 Monitori…

eess.AS2020

Anomalous sound detection based on interpolation deep neural network

Kaori Suefusa, Tomoya Nishida, Harsh Purohit +3

As the labor force decreases, the demand for labor-saving automatic anomalous sound detection technology that conducts maintenance of industrial equipment has grown. Conventional a…