IDMT-DESED-FL

sounds

General information

Label Value Description
Name IDMT-DESED-FL Full dataset name
ID sounds/idmt_desed_fl Datalist id for external indexing
Abbreviation IDMT-DESED-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-DESED-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
  • apartment room
  • computer interior
  • computer lab
  • emergency staircase
  • library

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
Hierarchical No
Instance