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Dataset-AOB: urban sounds events classification

Dataset-AOB is an audio dataset for urban sound events classification, containing 10 sound event classes, created by Ospina in a master's thesis.

AccessFree to access
LicenceLicense statement is still being checked
ProducerOspina, A.

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Key facts

InstitutionBeuth University of Applied Sciences, Berlin
Coverageurban sound events
Time span2020
Scale6 files, 5049 audio samples (4831 development, 218 evaluation)

Contents & fields

The dataset contains 10 urban sound event classes: alarm-siren, children playing, dog bark, engine, footsteps, glass breaking, gun shot, metro train, rain, screams. Audio format is .wav, duration < 4 seconds, sampling rate 22KHz-44KHz. Development set: 4831 samples, evaluation set: 218 samples. Includes metadata (.csv) and source distribution per class (.png).

  • alarm-siren——alarm/siren sound
  • children playing——children playing sound
  • dog bark——dog barking sound
  • engine——engine sound
  • footsteps——footsteps sound
  • glass breaking——glass breaking sound
  • gun shot——gun shot sound
  • metro train——metro train sound
  • rain——rain sound
  • screams——screaming sound

Research uses

Suitable for urban sound event classification, deep learning audio recognition, environmental sound analysis, etc.

Information comes from the source page. Please check that page for current details and terms.

Keywords

urban soundaudio classificationdeep learningsound eventdataset

Access and licence

Licence: License statement is still being checked · Source page
Rights details not yet verified
| Free to access

Why this is hard to get on your own

When obtaining audio data for urban sound event classification, one often needs a well-labeled, balanced dataset with clear license.

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