Robust Polyphonic MIDI Score Following with Hidden Markov Models

Although modern audio score following systems work very well with low polyphonic performances, they are still too imprecise with highly polyphonic instruments such as the piano, or the guitar. On the other hand, these instruments can easily output Midi information which shows that our work on robust Midi score following is still needed. We propose an adaption to Midi input of our HMM-based stochastic audio score follower, focusing the attention to the piano as our test instrument. The acoustic salience of the performance is modeled taking into account the particularities of piano note envelopes, from which note match and attack probabilities are derived. Tests with a complex piano piece played with many errors showed a very high robustness.