Note:
This bibliographic page is archived and will no longer be updated.
For an up-to-date list of publications from the Music Technology Group see the
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Identifying saxophonists from their playing styles
| Title | Identifying saxophonists from their playing styles |
| Publication Type | Conference Paper |
| Year of Publication | 2007 |
| Conference Name | 30th AES Conference |
| Authors | Ramirez, R. , Maestre E. , & Pertusa A. |
| Abstract | This paper describes a machine learning approach to the problem of identifying professional musicians from their playing style. We focus on the identification of jazz saxophonists by studying their expressive characteristics. In particular, we investigate expressive deviations of parameters such as pitch, timing, amplitude and timbre in monophonic audio recordings. We describe how we extract a symbolic description from the audio recordings and how we use this symbolic description to train a performance-based interpreter classifier. |
