TAU Spatial Sound Events 2019 - Ambisonic and Microphone Array, Evaluation Datasets

sounds

General information

Label Value Description
Name TAU Spatial Sound Events 2019 - Ambisonic and Microphone Array, Evaluation Datasets Full dataset name
ID sounds/tau_spatial_events_2019_eval Datalist id for external indexing
Abbreviation TAU-SELD2019-EVAL 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 Spatial Sound Events Common name for all related datasets, used to group datasets coming from same source
Research domain SED SELD Synthetic Strong annotation Multi-channel 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 (2GB)
Citation [Adavanne2019] A multi-room reverberant dataset for sound event localization and detection

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
Sampling rate (kHz) 48 kHz Sampling rate in kHz, possible values: 8 | 16 | 22.05 | 32 | 44.1 | 48
Channels
Setup Ambisonic Array Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable
Number of channels 4
Material
Source Original Possible values: Original | Youtube | Freesound | Online | Crowdsourced | [Dataset name]
Variability sources Room impulse response Spatial location Possible values: Country | City | Location | Position | Device

Content

Content type Synthetic Possible values: Freefield | Synthetic | Isolated
Scene Constant Is the scene class constant for single recording, possible values: Constant | Variable
Event / Spatial location Constant Possible values: Constant | Moving | Unknown

Recording

Setup Unknown 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 100 files Total number of files
Total duration (minutes) 100 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) 60 sec Approximate length of files

Meta

Label Value Description
Types Event Spatial location 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 True Possible values: True | False | Almost
Classes
  • Indoor corridor
  • Indoor cafeteria
  • Indoor common area

Event

Classes 11 Number of event classes
Classes True Possible values: True | False | Almost
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

Cross-validation setup

Label Value Description
Provided No

Baseline

Label Value Description
Download Download Link to baseline system source code
Citation [Adavanne2018] Paper to cite for the baseline

Info

Label Value Description
Evaluation campaign DCASE2019 task3 Evaluation campaigns where the dataset was used.