General information |
| Label |
Value |
Description |
|
Name |
IDMT-URBAN-FL |
Full dataset name |
|
ID |
sounds/idmt_urban_fl
|
Datalist id for external indexing |
|
Abbreviation |
IDMT-URBAN-FL |
Official dataset abbreviation, e.g. one used in the original paper |
|
Provider |
Fraunhofer IDMT |
|
|
Year |
2021 |
Dataset release year |
|
Modalities |
Audio
|
Data modalities included in the dataset |
|
Collection name |
IDMT-URBAN-FL |
Common name for all related datasets, used to group datasets coming from same source |
|
Research domain |
SED
FL
|
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
(None)
|
|
|
Companion site |
Site
|
Link to the companion site for the dataset |
|
Citation |
[Johnson2021] DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection
|
|
Audio |
| Label |
Value |
Description |
|
Data |
|
|
Data type |
Audio
|
Possible values: Audio | Features |
|
|
File format |
|
|
Channels |
|
|
Material |
|
Content |
|
|
Content type |
Synthetic
|
Possible values: Freefield | Synthetic | Isolated |
|
Recording |
|
Files |
|
|
Count |
30000 files |
Total number of files |
|
|
Total duration (minutes) |
5000 min |
Total duration of the dataset in minutes |
|
|
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 |
None
|
List of meta data types provided for the data, possible values: Event, Tag, Scene, Caption, Geolocation, Spatial location, Annotator, Timestamp, Presence, Proximity, etc. |
|
Scene |
|
|
Classes |
5 |
Number of scene classes |
|
|
Classes |
- birds
- crowd
- fountain
- rain
- traffic
|
|
|
Event |
|
|
Classes |
10 |
Number of event classes |
|
|
Classes |
- air conditioner
- car horn
- children playing
- dog bark
- drilling
- engine idling
- gun shot
- jackhammer
- siren
- street music
|
|
|
|
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 |
|
|
|
Hierarchical |
No
|
|
|
|
Instance |