التفاصيل البيبلوغرافية
| العنوان: |
DCASE 2020 Challenge Task 2 Development Dataset |
| المؤلفون: |
Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto, Toshiki Nakamura, Yuki Nikaido, Ryo Tanabe, Harsh Purohit, Kaori Suefusa, Takashi Endo, Masahito Yasuda, Noboru Harada |
| بيانات النشر: |
Zenodo |
| سنة النشر: |
2020 |
| المجموعة: |
Zenodo |
| مصطلحات موضوعية: |
anomaly detection, acoustic condition monitoring, sound, machine fault diagnosis, machine learning, unsupervised learning, acoustic scene classification, acoustic signal processing, DCASE, computational auditory scene analysis, audio |
| الوصف: |
Description This dataset is the "development dataset" for the DCASE 2020 Challenge Task 2 "Unsupervised Detection of Anomalous Sounds for Machine Condition Monitoring" [task description] . The data comprises parts of ToyADMOS and the MIMII Dataset consisting of the normal/anomalous operating sounds of six types of toy/real machines. Each recording is a single-channel (proximately) 10-sec length audio that includes both a target machine's operating sound and environmental noise. The following six types of toy/real machines are used in this task: Toy-car (ToyADMOS) Toy-conveyor (ToyADMOS) Valve (MIMII Dataset) Pump (MIMII Dataset) Fan (MIMII Dataset) Slide rail (MIMII Dataset) Recordingprocedure The ToyADMOS consists of normal/anomalous operating sounds of miniature machines (toys) collected with four microphones, and the MIMII dataset consists of those of real-machines collected with eight microphones. Anomalous sounds in these datasets were collected by deliberately damaging target machines. For simplifying the task, we used only the first channel of multi-channel recordings; all recordings are regarded as single-channel recordings of a fixed microphone. The sampling rate of all signals has been downsampled to 16 kHz. From ToyADMOS, we used only IND-type data that contain the operating sounds of the entire operation (i.e., from start to stop) in a recording. We mixed a target machine sound with environmental noise, and only noisy recordings are provided as training/test data. For the details of the recording procedure, please refer to the papers of ToyADMOS and MIMII Dataset . Data We first define two important terms in this task: Machine Type and Machine ID. Machine Type means the kind of machine, which in this task can be one of six: toy-car, toy-conveyor, valve, pump, fan, and slide rail. Machine ID is the identifier of each individual of the same type of machine, which in the training dataset can be of three or four.Each machine ID's dataset consists of (i) around 1,000 samples of normal sounds for training ... |
| نوع الوثيقة: |
other/unknown material |
| اللغة: |
unknown |
| Relation: |
https://zenodo.org/communities/dcase; https://doi.org/10.5281/zenodo.3678170; https://doi.org/10.5281/zenodo.3678171; oai:zenodo.org:3678171 |
| DOI: |
10.5281/zenodo.3678171 |
| الاتاحة: |
https://doi.org/10.5281/zenodo.3678171 |
| Rights: |
info:eu-repo/semantics/openAccess ; Creative Commons Attribution Non Commercial Share Alike 4.0 International ; https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode |
| رقم الانضمام: |
edsbas.D915C10C |
| قاعدة البيانات: |
BASE |