TAU Urban Acoustic Scenes 2019 Openset, Development dataset

scenes

General information

Label Value Description
Name TAU Urban Acoustic Scenes 2019 Openset, Development dataset Full dataset name
ID scenes/tau_asc_2019_openset_dev Datalist id for external indexing
Abbreviation TAU-ASC2019-OPEN-DEV Official dataset abbreviation, e.g. one used in the original paper
Provider TAU
Year 2019 Dataset release year
Modalities Audio Data modalities included in the dataset
Collection name TAU Urban Acoustic Scenes Common name for all related datasets, used to group datasets coming from same source
Research domain ASC Open set 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 (17.8GB)
Citation [Mesaros2018] A multi-device dataset for urban acoustic scene classification

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 Mono Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable
Number of channels 1
Material
Source Original Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name]
Variability sources Country City Location Position Possible values: Country | City | Location | Position | Device

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
Setup count 1 Amount of different recording setups (microphone and recording device) used
Spot type Fixed Possible values: Fixed | Moving | Unknown

Files

Count 15850 files Total number of files
Total duration (minutes) 2642 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 Scene 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 11 Number of scene classes
Classes True Possible values: True | False | Almost
Classes
  • airport
  • bus
  • metro station
  • metro
  • park
  • public square
  • shopping mall
  • street traffic
  • street pedestrian
  • tram
  • unknown
Annotation
Type Weak Possible values: Strong | Weak | None
Source Location Possible values: Experts | Crowdsourced | Synthetic | Location
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
Labeling
Hierarchical No
Instance
Count 15850 Count of all scene instances in the dataset

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

Info

Label Value Description
Evaluation campaign DCASE2019 task1C Evaluation campaigns where the dataset was used.