TUT Sound events 2017, Development dataset

sounds

General information

Label Value Description
Name TUT Sound events 2017, Development dataset Full dataset name
ID sounds/tut_sound_events_2017_dev Datalist id for external indexing
Abbreviation TUT-SED2017-DEV Official dataset abbreviation, e.g. one used in the original paper
Provider TUT
Year 2017 Dataset release year
Modalities Audio Data modalities included in the dataset
Collection name TUT Sound events Common name for all related datasets, used to group datasets coming from same source
Research domain SED Strong annotation Street 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 Free
Download Download (1.3GB)
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
File format wav Possible value: wav | aiff | flac | mp3 | aac | ogg
Lossy compression No is audio compressed in a lossy manner
Bit rate 24 Bit depth of audio, possible values: 8 | 16 | 24 | 32
Sampling rate (kHz) 44.1 kHz Sampling rate in kHz, possible values: 8 | 16 | 22.05 | 32 | 44.1 | 48
Channels
Setup Binaural Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable
Number of channels 2
Material
Source Original Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name]

Content

Content type Freefield Possible values: Freefield | Synthetic | Isolated
Scene Constant Is the scene class constant for single recording, possible values: Constant | Variable

Recording

Setup Uncontrolled Possible values: Near-field | Far-field | Mixed | Uncontrolled | Unknown
Spot type Fixed Possible values: Fixed | Moving | Unknown

Files

Count 24 files Total number of files
Total duration (minutes) 92 min Total duration of the dataset in minutes
File length Variable Characterization of the file lengths, possible values: Constant | Quasi-constant | Variable
File length (seconds) 180-300 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

Classes 1 Number of scene classes
Classes Street

Event

Classes 6 Number of event classes
Classes
  • brakes squeaking
  • car
  • children
  • large vehicle
  • people speaking
  • people walking
Annotation
Type Strong 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
Validated amount (%) 100 % Percentage of all data, amount of data which is validated by human
Strong annotations amount (%) 100 % Percentage of all data, amount of data which has strong annotations
Overlapping event instances Yes
Labeling
Hierarchical No
Instance
Count 729 Count of all event instances in the dataset
Average instances per class 121.5 Average per class instance count

Cross-validation setup

Label Value Description
Provided Yes
Folds 4
Sets Train Test Set types provided in the split, possible values: Train | Test | Val | Dev | Eval

Info

Label Value Description
Evaluation campaign DCASE2017 task3 Evaluation campaigns where the dataset was used.