A Review: Music Feature Extraction from an Audio Signal

Abstract

In recent years, the revenue earned through digital music stood at a billion-dollar market and the US remained the most profitable market for Digital music. Due to the digital shift, today people have access to millions of music clips from online music applications through their smart phones. In this context, there are some issues identified between the music listeners, music search engine by querying and retrieving music clips from a large collection of music data set. Classification is one of the fundamental problems in music information retrieval (MIR). Still, there are some hurdles according to their listener's preferences regarding music collections and their categorization. In this paper, different music extraction features are addressed, which can be used in various tasks related to music classification like a listener's mood, instrument recognition, artist identification, genre, query-by-humming, and music annotation. This review illustrates various features that can be used for addressing the research challenges posed by music mining.

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