/Urban_Sound_Classification

Classify different urban sounds as air_conditioner, car_horn, children_playing, dog_bark, drilling, engine_idling, gun_shot, jackhammer, siren, street_music using Convolutional Neural Networks (CNNs).

Primary LanguageJupyter Notebook

Urban_Sound_Classification

Aim of this project was to classify different urban sounds as air_conditioner, car_horn, children_playing, dog_bark, drilling, engine_idling, gun_shot, jackhammer, siren, street_music using Convolutional Neural Networks (CNNs).

This dataset contains 8732 labeled sound excerpts (<=4s) of urban sounds from 10 classes:

  • air_conditioner (0)
  • car_horn (1)
  • children_playing (2)
  • dog_bark (3)
  • drilling (4)
  • enginge_idling (5)
  • gun_shot (6)
  • jackhammer (7)
  • siren (8)
  • street_music (9)

In addition to the sound excerpts, a CSV file containing metadata about each excerpt is also provided, which includes:

  • slice_file_name: The name of the audio file. The name takes the following format: [fsID]-[classID]-[occurrenceID]-[sliceID].wav, where: [fsID] = the Freesound ID of the recording from which this excerpt (slice) is taken
    [classID] = a numeric identifier of the sound class (see description of classID below for further details)
    [occurrenceID] = a numeric identifier to distinguish different occurrences of the sound within the original recording
    [sliceID] = a numeric identifier to distinguish different slices taken from the same occurrence

  • fsID: The Freesound ID of the recording from which this excerpt (slice) is taken

  • start: The start time of the slice in the original Freesound recording

  • end: The end time of slice in the original Freesound recording

  • salience: A (subjective) salience rating of the sound. 1 = foreground, 2 = background.

  • fold: The fold number (1-10) to which this file has been allocated.

  • classID: A numeric identifier of the sound class:
    0 = air_conditioner
    1 = car_horn
    2 = children_playing
    3 = dog_bark
    4 = drilling
    5 = engine_idling
    6 = gun_shot
    7 = jackhammer
    8 = siren
    9 = street_music

  • class: The class name: air_conditioner, car_horn, children_playing, dog_bark, drilling, engine_idling, gun_shot, jackhammer, siren, street_music.

This repository contains the following files:

  1. Code
    • Urban_Sound_Classification.ipynb
  2. Dataset
    • UrbanSound8K.csv
      (This file contains meta-data information about every audio file in the dataset whose link is given at the last.)
  3. README

Here's the link to the dataset:
https://www.kaggle.com/chrisfilo/urbansound8k
https://urbansounddataset.weebly.com/urbansound8k.html