MUSART: Music Retrieval Via Aural Queries
نویسنده
چکیده
MUSART is a research project developing and studying new techniques for music information retrieval. The MUSART architecture uses a variety of representations to support multiple search modes. Progress is reported on the use of Markov modeling, melodic contour, and phonetic streams for music retrieval. To enable large-scale databases and more advanced searches, musical abstraction is studied. The MME subsystem performs theme extraction, and two other analysis systems are described that discover structure in audio representations of music. Theme extraction and structure analysis promise to improve search quality and support better browsing and “audio thumbnailing.” Integration of these components within a single architecture will enable scientific comparison of different techniques and, ultimately, their use in combination for improved performance and functionality.
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Computer Music Journal Roger B. Dannenberg,* William P. Birmingham,† George Tzanetakis,†† Colin Meek,§ Ning Hu,* and Bryan Pardo¶ *School of Computer Science Carnegie Mellon University Pittsburgh, Pennsylvania 15213 USA {roger.dannenberg, ning.hu}@cs.cmu.edu †Math and Computer Science Department Grove City College Grove City, Pennsylvania 16127 USA [email protected] ††Computer Science Depart...
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تاریخ انتشار 2001