General information |
Label |
Value |
Description |
|
Name |
WildDESED |
Full dataset name |
|
ID |
sounds/wild_desed
|
Datalist id for external indexing |
|
Abbreviation |
WildDESED |
Official dataset abbreviation, e.g. one used in the original paper |
|
Provider |
Fortemedia |
|
|
Year |
2024 |
Dataset release year |
|
Modalities |
Audio
|
Data modalities included in the dataset |
|
Collection name |
WildDESED |
Common name for all related datasets, used to group datasets coming from same source |
|
Research domain |
SED
Noisy
|
Related domains, e.g., Scenes, Mobile devices, Audio-visual, Open set, Ambient noise, Unlabelled, Multiple sensors, SED, SELD, Tagging, FL, Strong annotation, Weak annotation, Unlabelled, Multi-annotator |
|
Related datasets name |
|
|
|
License |
Creative Commons, CC BY-SA 4.0 |
|
|
Download |
Download
(15.4GB)
|
|
|
Companion site |
Site
|
Link to the companion site for the dataset |
|
Citation |
[Xiao2024] WildDESED:An LLM-Powered Dataset for Wild Domestic Environment Sound Event Detection System
|
|
Audio |
Label |
Value |
Description |
|
Data |
|
|
Data type |
Audio
|
Possible values: Audio | Features |
|
|
File format |
|
|
|
File format type |
Constant
|
Possible values: Constant | Variable |
|
|
|
File format |
wav
|
Possible value: wav | aiff | flac | mp3 | aac | ogg |
|
|
|
Sampling rate (kHz) |
16 kHz |
Sampling rate in kHz, possible values: 8 | 16 | 22.05 | 32 | 44.1 | 48 |
|
|
Channels |
|
|
|
Setup |
Mono
|
Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable |
|
|
Material |
|
|
|
Source |
DESED
Youtube
Audioset
|
Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name] |
|
Content |
|
|
Content type |
Synthetic
|
Possible values: Freefield | Synthetic | Isolated |
|
Recording |
|
Files |
|
|
File length |
Constant
|
Characterization of the file lengths, possible values: Constant | Quasi-constant | Variable |
|
|
File length (seconds) |
10 sec |
Approximate length of files |
Meta |
Label |
Value |
Description |
|
Types |
Event
|
List of meta data types provided for the data, possible values: Event, Tag, Scene, Caption, Geolocation, Spatial location, Annotator, Timestamp, Presence, Proximity, etc. |
|
Scene |
|
Event |
|
|
Classes |
10 |
Number of event classes |
|
|
Classes |
- alarm bell
- blender
- cat
- dog
- dishes
- electric shaver/toothbrush
- frying
- running water
- speech
- vacuum cleaner
|
|
|
|
Annotation |
|
|
|
Type |
Strong
|
Possible values: Strong | Weak | Location | None |
|
|
|
Source |
Synthetic
|
Possible values: Experts | Crowdsourced | Synthetic | Metadata | Automatic |
|
|
|
Annotations per item |
1 |
How many annotations there are available per item (possible multi-annotator setup) |
|
|
|
Labelled amount (%) |
100 % |
Percentage of all data, amount of data which is labelled |
|
|
|
Strong annotations amount (%) |
100 % |
Percentage of all data, amount of data which has strong annotations |
|
|
|
Overlapping event instances |
Yes
|
|
|
|
Labeling |
|
|
Instance |
Cross-validation setup |
Label |
Value |
Description |
|
|
Provided |
Yes
|
|
|
|
Sets |
Train
Test
Val
|
Set types provided in the split, possible values: Train | Test | Val | Dev | Eval |