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Merged-Output Hidden Markov Model for Score Following of MIDI Performance with Ornaments, Desynchronized Voices, Repeats and Skips

A score-following algorithm for polyphonic MIDI performances is presented that can handle performance mistakes, ornaments, desynchronized voices, arbitrary repeats and skips. The algorithm is derived from a stochastic performance model based on hidden Markov model (HMM), and we review the recent development of model construction. In this paper, the model is further extended to capture the multi-voice structure, which is necessary to handle note reorderings by desynchronized voices and widely stretched ornaments in polyphony. For this, we propose mergedoutput HMM, which describes performed notes as merged outputs frommultiple HMMs, each corresponding toa voice part. It is confirmed that the model yields a score-following algorithm which is effective under frequent note reorderings across voices and complicated ornaments.