Audio classification using ML methods
This is an incremental application of existing machine learning methods to a specific audio classification task.
The paper tackled music genre classification by applying multiple supervised learning algorithms to audio features, achieving classification into classical and metal genres.
Machine Learning systems have achieved outstanding performance in different domains. In this paper machine learning methods have been applied to classification task to classify music genre. The code shows how to extract features from audio files and classify them using supervised learning into 2 genres namely classical and metal. Algorithms used are LogisticRegression, SVC using different kernals (linear, sigmoid, rbf and poly), KNeighborsClassifier , RandomForestClassifier, DecisionTreeClassifier and GaussianNB.