Quantitative characterisation of audio data by ordinal symbolic dynamics
| Autor: | Wolfram Bunk, José M. Amigó, Thomas Aschenbrenner, Roberto A. Monetti |
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| Rok vydání: | 2013 |
| Předmět: |
Scheme (programming language)
Theoretical computer science Computer science Feature vector Fingerprint (computing) Complex system Symbolic dynamics General Physics and Astronomy Field (computer science) Violin Support vector machine General Materials Science Physical and Theoretical Chemistry computer computer.programming_language |
| Zdroj: | The European Physical Journal Special Topics. 222:473-485 |
| ISSN: | 1951-6401 1951-6355 |
| Popis: | Ordinal symbolic dynamics has developed into a valuable method to describe complex systems. Recently, using the concept of transcripts, the coupling behaviour of systems was assessed, combining the properties of the symmetric group with information theoretic ideas. In this contribution, methods from the field of ordinal symbolic dynamics are applied to the characterisation of audio data. Coupling complexity between frequency bands of solo violin music, as a fingerprint of the instrument, is used for classification purposes within a support vector machine scheme. Our results suggest that coupling complexity is able to capture essential characteristics, sufficient to distinguish among different violins. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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