Enhancing Music Classification: Machine Learning Approaches to Song Type Recognition

Abstract

Listen

Translate article

In this paper, a new method for identifying Indian music inside a machine intelligence framework is presented using digital signal processing (DSP) techniques. To extract useful information from audio signals, the suggested method makes use of aspects specific to Indian music, like pitch, tempo, and spectral characteristics. Several DSP methods are used to efficiently handle the audio data, such as spectrogram analysis and Fourier transformations. Furthermore, machine learning models are used for pattern recognition and classification tasks. Examples of these models are deep neural networks and support vector machines. Accurate identification of Indian music is made possible by the combination of DSP and machine intelligence, especially in the face of noise or stylistic changes in performance. The suggested method is effective in identifying Indian music, as shown by the experimental results, which also highlight its potential uses in content indexing, music recommendation systems, and cultural preservation initiatives.