DCASE2017 task 4 development dataset

sounds

General information

Label Value Description
Name DCASE2017 task 4 development dataset Full dataset name
ID sounds/dcase2017_task4_dev Datalist id for external indexing
Abbreviation DCASE2017-WSED-DEV Official dataset abbreviation, e.g. one used in the original paper
Provider DCASE
Year 2017 Dataset release year
Modalities Audio Video Data modalities included in the dataset
Collection name DCASE2017-WSED Common name for all related datasets, used to group datasets coming from same source
Research domain SED Street Strong annotation Weak annotation Audio-visual 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
License Youtube
Download Download (None)
Companion site Site Link to the companion site for the dataset
Citation [Mesaros2017] DCASE 2017 challenge setup: tasks, datasets and baseline system

Audio

Label Value Description

Data

Data type Audio Possible values: Audio | Features
File format
File format type Constant Possible values: Constant | Variable
Lossy compression Yes is audio compressed in a lossy manner
Channels
Setup Mono Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable
Number of channels 1
Material
Source Youtube Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name]

Content

Content type Freefield Possible values: Freefield | Synthetic | Isolated

Recording

Setup Unknown Possible values: Near-field | Far-field | Mixed | Uncontrolled | Unknown

Files

Count 51660 files Total number of files
Total duration (minutes) 8460.3 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 Event Tag 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 1 Number of scene classes
Classes True Possible values: True | False | Almost
Classes
  • Street

Event

Classes 17 Number of event classes
Annotation
Type Strong Weak Possible values: Strong | Weak | Location | None
Source Experts 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 (%) 1.33 % Percentage of all data, amount of data which has strong annotations
Overlapping event instances Yes
Labeling
Hierarchical No
Instance
Count 56737 Count of all event instances in the dataset
Average instances per class 3337.5 Average per class instance count

Cross-validation setup

Label Value Description
Provided Yes
Folds 1
Sets Train Test Set types provided in the split, possible values: Train | Test | Val | Dev | Eval

Baseline

Label Value Description
Download Download Link to baseline system source code
Citation [Mesaros2017] Paper to cite for the baseline

Info

Label Value Description
Evaluation campaign DCASE2017 task4 Evaluation campaigns where the dataset was used.