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While YQX's performances may not exactly command our admiration, they are certainly not unmusical (for the most part), they seem to betray some musical understanding, and they are sometimes surprising.
The previous analysis of the Chopin performance seems to suggest that YQX has a sense of unity and coherence, variation, and so on.
With YQX, we have no idea why the system chose to do what it did.
YQX does a number of things that are not prescribed in the score, that could not be predicted by the authors, but are nevertheless musically sensible and may even be ascribed a certain aesthetic quality.
YQX was developed not as a dedicated tool, with the purpose of winning Rencon contests, but as part of a much larger and broader basic research effort that aims at elucidating the elusive art of expressive music performance.
Generally, the strategy is to extend YQX step by step, so that we can quantify exactly the relevance of the various components and layers of the model, by measuring the improvement in the model's prediction power relative to real performance data.
The first is to extend YQX with a notion of local temporal contexts.
The second major direction for extending YQX is towards multiple structural levels.
State-of-the-art systems like YQX can even produce expressive performances themselves that, while neither truly high-class nor arguably very creative, could pass as the products of a mediocre music student.
See The Core of YQX: A Simple Bayesian Model in this article for an explanation of these.
(6.) We are insinuating purposeful behavior by YQX here, which we will be quick to dismiss in the following section.
(7.) Viewing the videos, the reader will have noticed that both in the Chopin and the Mozart, YQX makes a couple of annoying octave transposition errors (in the octava (8va) passages).
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