EconStor >
Technische Universität Dortmund >
Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen, Technische Universität Dortmund >
Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/22580
  
Title:Identification of Musical Instruments by means of the Hough-Transformation PDF Logo
Authors:Klefenz, Frank
Röver, Christian
Weihs, Claus
Issue Date:2004
Series/Report no.:Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2004,67
Abstract:In order to distinguish between the sounds of different musical instruments, certain instrument-specific sound features have to be extracted from the time series representing a given recorded sound. The Hough Transform is a pattern recognition procedure that is usually applied to detect specific curves or shapes in digital pictures (Shapiro, 1978). Due to some similarity between pattern recognition and statistical curve fitting problems, it may as well be applied to sound data (as a special case of time series data). The transformation is parameterized to detect sinusoidal curve sections in a digitized sound, the motivation being that certain sounds might be identified by certain oscillation patterns. The returned (transformed) data is the timepoints and amplitudes of detected sinusoids, so the result of the transformation is another ?condensed? time series. This specific Hough Transform is then applied to sounds played by different musical instruments. The generated data is investigated for features that are specific for the musical instrument that played the sound. Several classification methods are tried out to distinguish between the instruments and it turns out that RDA (a hybrid method combining LDA and QDA) (Friedman, 1989) performs best. The resulting error rate is better than those achieved by humans (Bruderer, 2003).
Document Type:Working Paper
Appears in Collections:Technical Reports, SFB 475: Komplexitätsreduktion in multivariaten Datenstrukturen, TU Dortmund

Files in This Item:
File Description SizeFormat
tr67-04.pdf272.51 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/22580

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.