/music-genre-classification

With day-by-day increasing internet penetration, huge amount of useful data is available at proximity to people. Although it seems that there is ease of access to data, but this exponentially increasing amount of data brings to table a new problem – most of this chunk is unclassified. Through this project, we aim to resolve this problem with something very close to people – music. We aim to explore various methodologies used to develop an automatic music genre classifier and thus, help in comparing efficiency to these methods.

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

Music-Genre-Classification

Description various files are given below

  • util.py-has functions to compute centroid and spread
  • plot.py- it is used to plot chromgram , time series of a given audio file
  • covar.py - it is used to compute covarince of feautes.
  • chroma_extract.py- it has functions to compute chromagram from time series
  • chroma_feature_extractor.py - it is used to extract centroid,spread,min ,max chroma
  • chroma_wide_feature_extractor- it used to extract mean and standard deviation from 10 frames of a chromagram.
  • classifer_1.0.py- used for classification
  • classifer_2.0.py -used for calssification
  • chroma_feature_avg.py- used for to average feature vectors over frames.