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Convolution Based Classification of Audio and Symbolic Representations of Music by doktemsahika is a document available to read on EtoBox.

What is Convolution Based Classification of Audio and Symbolic Representations of Music about?

The document presents a convolution-based method for classifying audio and symbolic representations of music, achieving state-of-the-art accuracy in distinguishing between composers like Haydn and Mozart. The method utilizes pitch-time representations, Gaussian filtering, and various classification algorithms, demonstrating effectiveness across both audio and symbolic data. Experimental results indicate that the approach can equally classify music styles and identify specific pieces, such as preludes and fu

Author

doktemsahika

Language

EN