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Evaluation of Weighted Principal-Component Analysis Matching for Wavetable Synthesis

[Engineering Report] Wavetable matching of musical instrument tones using principal-component analysis (PCA) takes advantage of spectral correlation information to find the basis spectra. Although PCA matching is efficient, it usually matches the low-amplitude parts of a tone poorly because of its inherent statistical bias. Weighted PCA methods are described, which normalize the tone prior to PCA to fairly weight its different parts. Matching results for a range of instruments show that the PCA of a frame-weighted spectrum with a roughly constant loudness throughout improves on unweighted PCA by an average of about 4% relative spectral error. Listening test results show that frame-weighted PCA gives some perceptual improvements for most of the instruments.

Authors: Wun, Simon; Horner, Andrew
Affiliations: Sound and Interactivity Project, Institute for Infocomm Research, Singapore ; Department of Computer Science, Hong Kong University of Science and Technology, Kowloon, Hong Kong(See document for exact affiliation information.)
JAES Volume 55 Issue 9 pp. 762-774; September 2007 Import into BibTeX

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