Freiburg-106, Audio Data Set for Human Activity Recognition

sounds

General information

Label Value Description
Name Freiburg-106, Audio Data Set for Human Activity Recognition Full dataset name
ID sounds/freiburg106 Datalist id for external indexing
Abbreviation Freiburg-106 Official dataset abbreviation, e.g. one used in the original paper
Provider Freiburg
Year 2012 Dataset release year
Modalities Audio Data modalities included in the dataset
Collection name Freiburg-106 Common name for all related datasets, used to group datasets coming from same source
Research domain Tagging Weak annotation Isolated sounds Human activity Kitchen 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
Download Download (375MB)
Companion site Site Link to the companion site for the dataset
Citation [Stork2012] Audio-based human activity recognition using Non-Markovian Ensemble Voting

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 16 Bit depth of audio, possible values: 8 | 16 | 24 | 32
Sampling rate (kHz) 22.05 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]

Content

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

Files

Count 1524 files Total number of files
Total duration (minutes) 54 min Total duration of the dataset in minutes
File length Variable Characterization of the file lengths, possible values: Constant | Quasi-constant | Variable

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 True Possible values: True | False | Almost
Classes
  • kitchen

Event

Classes 24 Number of event classes
Classes False Possible values: True | False | Almost
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
Overlapping event instances No
Labeling
Hierarchical No
Instance
Count 1524 Count of all event instances in the dataset
Average instances per class 63.5 Average per class instance count

Info

Label Value Description
Comments Three test sequences provided