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Combining Score And Filter Based Models To Predict Tempo Fluctuations In Expressive Music Performances

Tempo variations in classical music are an important means of artistic expression. Fluctuations in tempo can be large and sudden, making applications like automated score following a challenging task. Some of the ﬂuctuations may be predicted from (tempo annotations in) the score, but prediction based only on the score is unlikely to capture the internal coherence of a performance. On the other hand, ﬁltering approaches to tempo prediction (like the Kalman ﬁlter) are suited to track gradual changes in tempo, but do not anticipate sudden changes. To combine the advantages of both approaches, we propose a method that incorporates score based tempo predictions into a Kalman ﬁlter model of performance tempo. We show that the combined model performs better than the ﬁlter model alone.