Musical Instrument Timbres Classification with Spectral Features
| Autor: | Giulio Agostini, Emanuele Pollastri, Maurizio Longari |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Musical instrument classification
Computer science Speech recognition Feature extraction audio features extraction lcsh:TK7800-8360 Musical instrument Musical Spectral centroid lcsh:Telecommunication Set (abstract data type) lcsh:TK5101-6720 Electrical and Electronic Engineering Representation (mathematics) timbre classification business.industry pattern recognition lcsh:Electronics Pattern recognition Quadratic classifier Support vector machine content-based audio indexing/searching Hardware and Architecture Signal Processing Inharmonicity Pattern recognition (psychology) Artificial intelligence business Timbre |
| Zdroj: | EURASIP Journal on Advances in Signal Processing, Vol 2003, Iss 1, p 943279 (2003) EURASIP Journal on Advances in Signal Processing, Vol 2003, Iss 1, Pp 5-14 (2003) MMSP |
| ISSN: | 1687-6180 |
| DOI: | 10.1155/s1110865703210118 |
| Popis: | A set of features is evaluated for recognition of musical instruments out of monophonic musical signals. Aiming to achieve a compact representation, the adopted features regard only spectral characteristics of sound and are limited in number. On top of these descriptors, various classification methods are implemented and tested. Over a dataset of 1007 tones from 27 musical instruments, support vector machines and quadratic discriminant analysis show comparable results with success rates close to 70% of successful classifications. Canonical discriminant analysis never had momentous results, while nearest neighbours performed on average among the employed classifiers. Strings have been the most misclassified instrument family, while very satisfactory results have been obtained with brass and woodwinds. The most relevant features are demonstrated to be the inharmonicity, the spectral centroid, and the energy contained in the first partial. |
| Databáze: | OpenAIRE |
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