JSM 2004 - Toronto

Abstract #302155

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Activity Number: 90
Type: Contributed
Date/Time: Monday, August 9, 2004 : 9:00 AM to 10:50 AM
Sponsor: Section on Statistical Computing
Abstract - #302155
Title: Matrix Valued General Linear Modeling of Music Instrumentation Digital Interface Data
Author(s): Lisa Cannon and Cecil R. Hallum*+
Companies: Sam Houston State University and Sam Houston State University
Address: Dept. of Mathematics and Statistics, Huntsville, TX, 77341,
Keywords: linear models ; multivariate analysis ; MIDI ; generalized inverses ; matrix differentials
Abstract:

Music Instrumentation Digital Interface MIDI) data is music data in multivariate form. Each musical tune is expressible as a matrix with each column comprising the frequencies of play for each instrument for each clock beat in time. This paper utilizes multivariate statistical techniques and linear algebraic structures to attain unique insights into MIDI music. Matrix differentials and generalized inverses provide opportunities in matrix-valued linear modeling of these MIDI tunes to investigate the relationship between differing tunes, artists, music categories, etc. Applications resulting from converting vector-valued data into sound/music forms are included and discussed particularly as relates to assisting seeing-impaired individuals "hear" critical information in vector-valued data.

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