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A Comprehensive and Modular Framework for Audio Content Extraction, Aimed at Research, Pedagogy, and Digital Library Management
We present a framework for audio analysis and the extraction of low-level features, mid-level structures and high-level concepts, altogether studied as a fully interwoven complex system. Composite operations are constructed via an intuitive programming language on top of Matlab. Datasets of any size can be processed thanks to implicit memory management mechanisms. The data structure enables a tight articulation between signal and symbolic layers in a unified framework. The resulting technology can be used as a pedagogical tool for the understanding of audio, speech and musical processes and concepts, and for content-based discovery of digital libraries. Other applications includes intelligent browsing and structuring of digital library, information retrieval, and the design of content-based audio interfaces.
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