automatic musical genre classification of audio signals

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Automatic Music Genre Classification of Audio Signals with

This paper presents a comprehensive machine learning approach to the problem of automatic musical genre classification using the audio signal The proposed approach uses two feature vectors Support vector machine classifier with polynomial kernel function and machine learning algorithms

How are audio signals classified?
In , audio signals are segmented and classified into “music,” “speech,” “laughter,” and nonspeech sounds using cepstral coefficients and a hidden Markov model (HMM).
What is automatic musical genre classification?
Automatic musical genre classification can assist or replace the human user in this process and would be a valuable addition to music information retrieval systems. In addition, automatic musical genre classification provides a framework for developing and evaluating features for any type of content-based analysis of musical signals.
Can machine learning solve automatic musical genre classification using audio signal?
This paper presents a comprehensive machine learning approach to the problem of automatic musical genre classification using the audio signal. The proposed approach uses two feature vectors, Support vector machine classifier with polynomial kernel function and machine learning algorithms.
Can music genre classification be used in music recommendation systems?
The potential applications of music genre classification in music recommendation systems [ 4] and music streaming services [ 5] have led to extensive research in this area. Music genre classification typically involves two steps: acoustic feature extraction and classification.

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