license: cc-by-sa-4.0
annotations_creators:
- unknown
language_creators:
- unknown
size_categories:
- 100K<n<100M
source_datasets:
- unknown
task_categories:
- audio-classification
task_ids:
- other-audio-slot-filling
Dataset Card for audioset2022
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: AudioSet Ontology
- Repository: [Needs More Information]
- Paper: Audio Set: An ontology and human-labeled dataset for audio events
- Leaderboard: Paperswithcode Leaderboard
Dataset Summary
The AudioSet ontology is a collection of sound events organized in a hierarchy. The ontology covers a wide range of everyday sounds, from human and animal sounds, to natural and environmental sounds, to musical and miscellaneous sounds.
This repository only includes audio files for DCASE 2022 - Task 3
Supported Tasks and Leaderboards
audio-classification: The dataset can be used to train a model for Sound Event Detection/Localization.
The recordings only includes the single channel audio. For Localization tasks, it will required to apply RIR information
Languages
None
Dataset Structure
Data Instances
WIP
{
'file':
}
Data Fields
- file: A path to the downloaded audio file in .mp3 format.
Data Splits
This dataset only includes audio file from the unbalance train list. The data comprises two splits: weak labels and strong labels.
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
[Needs More Information]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
The dataset was initially downloaded by Nelson Yalta (nelson.yalta@ieee.org).
Licensing Information
Citation Information
@inproceedings{45857,
title = {Audio Set: An ontology and human-labeled dataset for audio events},
author = {Jort F. Gemmeke and Daniel P. W. Ellis and Dylan Freedman and Aren Jansen and Wade Lawrence and R. Channing Moore and Manoj Plakal and Marvin Ritter},
year = {2017},
booktitle = {Proc. IEEE ICASSP 2017},
address = {New Orleans, LA}
}