Musical Sentiment Recognition from Row Audio using Various Machine Learning Methods

Authors

  • Siddhartha Chaki Student, Department of MCA, Vivekanand Education Society’s Institute of Technology, Mumbai, India
  • Shivkumar Goel Professor, Department of MCA, Vivekanand Education Society’s Institute of Technology, Mumbai, India

Keywords:

Audio emotions/sentiment classification, Extreme Gradient Boosting, K-NN, Machine learning, Music information retrieval (MIS)

Abstract

The main objective of this paper is to present a Machine Learning model method to classify/tag any music based on its musical sentiment which it represents throughout each phase of time on it. In this paper, we try to map the emotions/moods with music using various machine learning methods. In preprocessing step its extracts various features like chroma frequencies, tonnetz, Mel-Frequency Cepstral Coefficients, root-mean-square energy, zero-crossing rate, spectral features collectively and their statistical calculations like mean, variance, min, max etc. At the final stage we apply various techniques to develop the best approach to solve this problem using extracted features.

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Published

2021-07-17

How to Cite

[1]
S. Chaki and S. Goel, “Musical Sentiment Recognition from Row Audio using Various Machine Learning Methods”, IJRESM, vol. 4, no. 7, pp. 146–148, Jul. 2021.

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Section

Articles