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.wav files, training dataset (MFCC), and graph plots (FFTs, MFCCs, Waveforms) from Latin America, Asia, MiddleEast, and Africa

Home Page: https://doi.org/10.7910/DVN/13BPFB

License: Other

Python 100.00%
audio-processing signal-processing dataset music music-library genre-classification genres-classification genre-suggestion harvard-dataverse africa asia mfcc lama classification genre sound

lama-music-genre-dataset's Introduction

LAMA : A World Music Genre Dataset

LAMA - LatinAmerica, Asia, MiddleEastern, Africa Genre Dataset

This Dataset consists of the .wav files, training dataset (MFCC), and graph plots (FFTs, MFCCs, STFTs, Waveforms) of YouTube videos classified into four categories: LatinAmerica, Asia, MiddleEastern, and Africa.

I hope that this work can help in several Deep Learning, Machine Learning projects in Music Genre Classification.

MusicGenreClassification

Anyone is free to use/change/contribute to this Dataset. Please cite if you use this Dataset in your research/projects.

Getting Started

Some data couldn't be uploaded to GitHub because the file size was too large. Instead, I attached a Harvard Dataverse link below to retrieve the data.

The data contained in LAMA can be classified into three categories:

  1. .wav files (Data_Original, Data_Cropped) -> Uploaded in Harvard Dataverse. Link below.
  2. Waveform, FFT, STFT, MFCC graph plots (Graphs, Sample_Graphs) -> Uploaded in Harvard Dataverse. Link below.
  3. mfcc training data (training_data.json)

Statistics

  • Data_Original : 113 (Africa), 83 (Asia), 90 (LatinAmerica), 80 (MiddleEast)
  • Data_Cropped (1 min clips of original) : 108 (Africa), 77 (Asia), 87 (LatinAmerica), 77 (MiddleEast)
  • Graphs -> FFT : 108 (Africa), 77 (Asia), 87 (LatinAmerica), 77 (MiddleEast)

Link to the full audio data

graph plot EXAMPLES:

from Graphs Image of SFTS from Sample_Graphs Image of MFCC

Acknowledgements

The classification of genre in this Dataset is mostly from the "AudioSet" project by the Sound and Video Understanding teams at Google Research. I chose the best examples from their website and preprocessed them to create this Dataset.

In addition, I obtained much of the knowledge needed to create this Dataset from the YouTube Channel, "Valerio Velardo - The Sound of AI. Mr. Velardo makes amazing videos, and I believe that he deserves more recognition.

Citing this DataSet

@data{DVN/13BPFB_2020,
author = {Lee, Bruce W},
publisher = {Harvard Dataverse},
title = {{LAMA World Music Genre Dataset}},
year = {2020},
version = {DRAFT VERSION},
doi = {10.7910/DVN/13BPFB},
url = {https://doi.org/10.7910/DVN/13BPFB}
}

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