Group5-CMLS-HW1

Music Genre Classification

{  10482867 10521088

   10539533  10702368

   10751919 } @mail.polimi.it

Project Workflow

Based on a subset of 400 audio pieces from GTZAN dataset

  • We build Model1: KNN Classifier, and Model2: SVC Classifier

  • Able to predict unseen audios among Blues, Metal, Hip-hop and Reggae

 

Preprocessing

  • retrieve annotations
  • check original dataset
  • split the dataset into training/test (80% vs. 20%)

Observe the Dataset

  • have a look at the data
  • check the quality

The Features 

  • 34 columns of feature
  • 400 audio tracks
  • 80 % for training
  • 20 % for testing
  • rescaling, selection, saving

Two Classifiers: KNN & SVC

  • The process to use the classifiers: pick the right parameters --> build the classifiers -->fit with training data set
  • We use K-fold (k = 10) Cross Validation and Grid Search method to optimise the parameters for those two classifiers

Results & Conclusions

  • Here are two confusion matrix to represent the final testing result, separately for  KNN and SVC

 

  • Each row in the matrix is the real genre, while each column is the predicted genre category classified by the model we build

Plot 4. KNN & SVC results of Confusion Matrix

Table 3: Final Results

Reference

  • [1]Data Sets. GTZAN Genre Collection.url:http : / / marsyas.info/downloads/datasets.html.

  • [2]LibROSA Documentation.url:https://librosa.github.io/librosa/.

  • [3]NumPy.url:https://numpy.org/.

  • [4]Pandas documentation.url:https://pandas.pydata.org/pandas-docs/stable/index.html.

  • [5]Scikit-learn.url:https://scikit-learn.org/stable/.

  • [6] Bob L. Sturm. “The GTZAN dataset: Itscontents, its faults, their effects on eval-uation, and its future use”. In:CoRRabs/1306.1461 (2013). arXiv:1306.1461.url:http://arxiv.org/abs/1306.1461.

  • [7] G. Tzanetakis and P. Cook. “Musicalgenre classification of audio signals”. In:IEEE Transactions on Speech and AudioProcessing10.5 (2002), pp. 293–302

  • [8] Final Detailed Report, Music Genre Classification, https://yilin10.github.io/MusicalGenreClassification/final.pdf

  • [9] Final Google Colab IPython Notebook, Music Genre Classification, https://github.com/yilin10/MusicalGenreClassification/blob/master/Assignment1.ipynb