Technical Reports - Query ResultsYour query term was 'number = 2004-07'
1 report found
- OFAI-TR-2004-07 ( 101kB g-zipped PostScript file, 87kB PDF file)
Learning to Play Mozart : Recent Improvements
- Asmir Tobudic, Gerhard Widmer
- This paper describes basic research on the crossroads between machine learning and musicology. Starting from a system which is able to automatically induce multi-level tempo and dynamics models of expressive performance from a large corpus of real performances by skilled pianists, we discuss several of its shortcomings and present improvements and their empirical evaluation. In particular, we show that in a such complex domain as a concert-class musical performance, one can treat the training data as noisy. Applying a standard machine learning technique for noise handling indeed significantly improve the results. We also discuss the major drawback of standard propositional k nearest neighbor algorithm in case of learning mutually dependent concepts on different levels of resolution and present our solution to these problems by introducing a new relational instance-based learning algorithm. It turns out that it is indeed able to overcome some of the weaknesses of its propositional counterpart.