Statistical Analysis of Musical Instruments | Zendy

Namunu C. Maddage | Zendy; Changsheng Xu | Zendy; ChinHui Lee | Zendy; Mohan Kankanhalli | Zendy; Qi Tian | Zendy

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Statistical Analysis of Musical Instruments

Author(s) -

Namunu C. Maddage,

Changsheng Xu,

ChinHui Lee,

Mohan Kankanhalli,

Qi Tian

Publication year - 2002

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-00262-6

DOI - 10.1007/3-540-36228-2_72

Subject(s) - computer science , mirroring , musical , speech recognition , parametric statistics , set (abstract data type) , domain (mathematical analysis) , parametric model , guitar , field (mathematics) , musical acoustics , signal (programming language) , artificial intelligence , acoustics , programming language , mathematics , art , mathematical analysis , statistics , physics , communication , sociology , pure mathematics , visual arts

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.

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