Download Nonlinear time series analysis of musical signals
In this work the techniques of chaotic time series analysis are applied to music. The audio stream from musical recordings are treated as representing experimental data from a dynamical system. Several performance of well-known classical pieces are analysed using recurrence analysis, stationarity measures, information metrics, and other time series based approaches. The benefits of such analysis are reported.
Download Towards Ontological Representations of Digital Audio Effects
In this paper we discuss the development of ontological representations of digital audio effects and provide a framework for the description of digital audio effects and audio effect transformations. After a brief account on our current research in the field of highlevel semantics for music production using Semantic Web technologies, we detail how an Audio Effects Ontology can be used within the context of intelligent music production tools, as well as for musicological purposes. Furthermore, we discuss problems in the design of such an ontology arising from discipline-specific classifications, such as the need for encoding different taxonomical systems based on, for instance, implementation techniques or perceptual attributes of audio effects. Finally, we show how information about audio effect transformations is represented using Semantic Web technologies, the Resource Description framework (RDF) and retrieved using the SPARQL query language.