CruiserX/sound-anomaly-detection-with-autoencoders

MIMII Sound Anomaly Detection with AutoEncoders

Goals

Requirements

Exploratory Data Analysis

Wave Forms

Short Time Fourier Transform

Spectrograms (dB Scale)

Mel-Spectrograms

Multiple Frames of Spectrograms

References

• MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection
• Harsh Purohit, Ryo Tanabe, Kenji Ichige, Takashi Endo, Yuki Nikaido, Kaori Suefusa, and Yohei Kawaguchi, “MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection,” in Proc. 4th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2019
• MIMII Dataset Baseline
• DCASE Challenge 2020: Unsupervised Detection of Anomalous Sounds for Machine Condition Monitoring
• Performing Anomaly Detection on Industrial Equipment Using Audio Signals