UrbanSound8K

sounds

General information

Label Value Description
Name UrbanSound8K Full dataset name
ID sounds/urbansound8k Datalist id for external indexing
Abbreviation UrbanSound8K Official dataset abbreviation, e.g. one used in the original paper
Provider NYU
Year 2014 Dataset release year
Modalities Audio Data modalities included in the dataset
Collection name UrbanSound Common name for all related datasets, used to group datasets coming from same source
Research domain Tagging Weak annotation Urban 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 Creative Commons
Download Download
Companion site Site Link to the companion site for the dataset
Citation [Salamon2014] A Dataset and Taxonomy for Urban Sound Research

Audio

Label Value Description

Data

Data type Audio Possible values: Audio | Features
File format
File format type Variable 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
Channels
Setup Variable Possible values: Mono | Stereo | Binaural | Ambisonic | Array | Multi-Channel | Variable
Material
Source Freesound 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
Spot type Unknown Possible values: Fixed | Moving | Unknown

Files

Count 8732 files Total number of files
Total duration (minutes) 525 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) 4 sec Approximate length of files

Meta

Label Value Description
Types 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 Street

Event

Classes 10 Number of event classes
Classes Almost Possible values: True | False | Almost
Classes
  • air conditioner
  • car horn
  • children playing
  • dog bark
  • drilling
  • engine idling
  • gun shot
  • jackhammer
  • siren
  • street music
Annotation
Type 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
Validated amount (%) 100 % Percentage of all data, amount of data which is validated by human
Strong annotations amount (%) 0 % Percentage of all data, amount of data which has strong annotations
Overlapping event instances No
Labeling
Hierarchical Yes
Ontology name Yes
Instance
Count 8732 Count of all event instances in the dataset
Average instances per class 873.2 Average per class instance count

Cross-validation setup

Label Value Description
Provided Yes
Folds 10
Sets Train Test Set types provided in the split, possible values: Train | Test | Val | Dev | Eval