30Aniket / 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).

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