Audio classification using ML methods

• URL: http://arxiv.org/abs/2305.19304v1
• Date: Tue, 30 May 2023 15:42:13 GMT
• Title: Audio classification using ML methods
• Authors: Krishna Kumar
• Abstract summary: 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 and DecisionTreeClassifier.
• Score: 2.132096006921048
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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