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Estimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies
| Title | Estimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies |
| Publication Type | Conference Paper |
| Year of Publication | 2004 |
| Conference Name | 5th International Society for Music Information Retrieval (ISMIR) Conference |
| Authors | Gómez, E. , & Herrera P. |
| Pagination | 92-95 |
| Abstract | In 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 document | http://mtg.upf.edu/system/files/publications/G%C3%B3mezHerrera-ISMIR-2004-page-92.pdf |
