105 citations · 159 across the 7 of their papers we have counts for
9 papers
MIMII-Gen: Generative Modeling Approach for Simulated Evaluation of Anomalous Sound Detection System
Harsh Purohit, Tomoya Nishida, Kota Dohi +2
Insufficient recordings and the scarcity of anomalies present significant challenges in developing and validating robust anomaly detection systems for machine sounds. To address th…
Anomalous Sound Detection Based on Machine Activity Detection
Tomoya Nishida, Kota Dohi, Takashi Endo +2
We have developed an unsupervised anomalous sound detection method for machine condition monitoring that utilizes an auxiliary task -- detecting when the target machine is active.…
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…
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…
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…
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…