Content-based music structure analysis

Ph.DDOCTOR OF PHILOSOPH

A SVM ¨C Based Classification Approach to Musical Audio

This paper describes an automatic heirarchical music classification approach based on support vector machines (SVM). Based on the proposed method, the music is classified into coursed classes such as vocal, instrumental or vocal mixed with instrumental music. These main classes are further sub-classed according to gender and instrument type. A novel method, Correction Algorithm for Music Sequence (CAMS) has been developed to imporve the classification efficiency

Statistical Analysis of Musical Instruments

Abstract. One important field in the research of computer music concerns the modeling of sounds. In order to design digital models mirroring as closely as possible a real sound and permitting in addition transformation by altering the synthesis parameters. We look for a signal model based on additive synthesis, whose parameters are estimated by the analysis of real sound. In this paper we present model-based analysis of musical notes generated by electric guitar. Both time domain and frequency domain feature analysis has been performed to find out the parameter selections for the musical signal analysis. Finally, non-parametric classification technique i.e. Nearest Neighbor Rule has been utilized to classify musical notes with this best set of parameters of the musical features. 1