Abstract
The paper concerns the use of multiple viewpoint representation schemes for prediction with statistical models of monophonic music. We present an experimental comparison of the performance of two techniques for combining predictions within the multiple viewpoint framework. The results demonstrate that a new technique based on a weighted geometric mean outperforms existing techniques. This finding is discussed in terms of previous research in machine learning.
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Pearce, M., Conklin, D., Wiggins, G. (2005). Methods for Combining Statistical Models of Music. In: Wiil, U.K. (eds) Computer Music Modeling and Retrieval. CMMR 2004. Lecture Notes in Computer Science, vol 3310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31807-1_22
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DOI: https://doi.org/10.1007/978-3-540-31807-1_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24458-5
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