Estimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies

TitleEstimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies
Publication TypeConference Paper
Year of Publication2004
Conference Name5th International Society for Music Information Retrieval (ISMIR) Conference
AuthorsGómez, E., & Herrera P.
Pagination92-95
AbstractIn this paper we evaluate two methods for key estimation from polyphonic audio recordings. Our goal is to compare between a strategy using a cognition-inspired model and several machine learning techniques to find a model for tonality (mode and key note) determination of polyphonic music from audio files. Both approaches have, as an input, a vector of values related to the intensity of each of the pitch classes of a chromatic scale. In this study, both methods are explained and evaluated in a large database of audio recordings of classical pieces.
preprint/postprint documenthttp://mtg.upf.edu/system/files/publications/G%C3%B3mezHerrera-ISMIR-2004-page-92.pdf
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