Audio Classification using modules called Librosa and scipy on Urban-Sound-8k dataset.
Link- https://urbansounddataset.weebly.com/download-urbansound8k.html
This dataset contains 8732 labeled sound excerpts (<=4s) of urban sounds from 10 classes: air_conditioner, car_horn, children_playing, dog_bark, drilling, enginge_idling, gun_shot, jackhammer, siren, and street_music. The classes are drawn from the urban sound taxonomy. 8732 audio files of urban sounds (see description above) in WAV format. The sampling rate, bit depth, and number of channels are the same as those of the original file uploaded to Freesound (and hence may vary from file to file).
This file contains meta-data information about every audio file in the dataset. This includes:
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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
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fsID: The Freesound ID of the recording from which this excerpt (slice) is taken
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start The start time of the slice in the original Freesound recording
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end: The end time of slice in the original Freesound recording
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salience: A (subjective) salience rating of the sound. 1 = foreground, 2 = background.
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fold: The fold number (1-10) to which this file has been allocated.
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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
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class: The class name: air_conditioner, car_horn, children_playing, dog_bark, drilling, engine_idling, gun_shot, jackhammer, siren, street_music.