Title
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection
Abstract
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 unsupervised anomaly detection, but it can fail at out-of-distribution detection since the likelihood is affected by the smoothness of the data. To improve the detection performance, we train the model to assign higher li...
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9414662
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Keywords
DocType
ISBN
Conferences,Estimation,Signal processing,Stability analysis,Acoustics,Task analysis,Speech processing
Conference
978-1-7281-7605-5
Citations 
PageRank 
References 
3
0.52
0
Authors
5
Name
Order
Citations
PageRank
Kota Dohi191.85
Takashi Endo2297.78
Purohit, H.3133.76
Ryo Tanabe4144.78
Yohei Kawaguchi5184.69