TUT-SED Synthetic 2016

sounds

Site Cakir2017

Label				Value	Description
General information
	Name			TUT-SED Synthetic 2016	Full dataset name
	ID			sounds/tut_synthetic_2016	Datalist id for external indexing
	Abbreviation			TUT-SED-SYNTH2016	Official dataset abbreviation, e.g. one used in the original paper
	Provider			TUT
	Year			2016	Dataset release year
	Modalities			Audio	Data modalities included in the dataset
	Collection name			TUT SED Synthetic 2016	Common name for all related datasets, used to group datasets coming from same source
	Research domain			SED Strong annotation Synthetic	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			Free
	Companion site			Site	Link to the companion site for the dataset
	Citation			[Cakir2017] Convolutional Recurrent Neural Networks forPolyphonic Sound Event Detection
Audio
Label				Value	Description
	Data
		Data type		Audio Features	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	16	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	BBC Sound Effects	Possible values: Original \| Youtube \| Freesound \| Online \| Crowdsourced \| [Dataset name]
			Variability sources	amplitude	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
	Recording
		Setup		Unknown	Possible values: Near-field \| Far-field \| Mixed \| Uncontrolled \| Unknown
	Files
		Count		100 files	Total number of files
		Total duration (minutes)		566 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)		337 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.
	Event
		Classes		16	Number of event classes
		Classes		Almost	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
			Count	36329	Count of all event instances in the dataset
			Average instances per class	2270.5625	Average per class instance count
Cross-validation setup
Label				Value	Description
		Provided		Yes
		Folds		1
		Sets		Train Val Test	Set types provided in the split, possible values: Train \| Test \| Val \| Dev \| Eval

TUT-SED Synthetic 2016

General information

Audio

Data

File format

Channels

Material

Content

Recording

Files

Meta

Event

Annotation

Labeling

Instance

Cross-validation setup