MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Task
Kota Dohi, Tomoya Nishida, Harsh Purohit, Ryo Tanabe, Takashi Endo,, Masaaki Yamamoto, Yuki Nikaido, and Yohei Kawaguchi

TL;DR
This paper introduces MIMII DG, a novel sound dataset designed to evaluate domain generalization methods for anomalous sound detection in industrial machines, addressing the challenge of unseen domain shifts.
Contribution
It provides the first dataset specifically for benchmarking domain generalization techniques in anomalous sound detection, including diverse domain shift scenarios and challenging background noise conditions.
Findings
Baseline experiments show the dataset effectively reproduces domain shifts.
The dataset is useful for benchmarking domain generalization techniques.
It highlights the difficulty of detecting certain domain shifts.
Abstract
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 degrade the detection performance, and handling them is a major issue for the application of ASD systems. While currently available datasets for ASD tasks assume that occurrences of domain shifts are known, in practice, they can be difficult to detect. To handle such domain shifts, domain generalization techniques that perform well regardless of the domains should be investigated. In this paper, we present the first ASD dataset for the domain generalization techniques, called MIMII DG. The dataset consists of five machine types and three domain shift scenarios for each machine type. The dataset is dedicated to the domain generalization task with features such as multiple different values for parameters that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMusic and Audio Processing · Speech Recognition and Synthesis · Speech and Audio Processing
