Realtime Audio to Score Alignment for Polyphonic Music Instruments, using Sparse Non-Negative Constraints and Hierarchical HMMS

Abstract

We present a new method for realtime alignment of audio to score for polyphonic music signals. In this paper, we will be focusing mostly on the multiple-pitch observation algorithm proposed based on realtime non-negative matrix factorization with sparseness constraints and hierarchical hidden Markov models for sequential modeling using particle filtering for decoding. The proposed algorithm has the advantage of having an explicit instrument model for pitch obtained through unsupervised learning as well as access to single note contribution probabilities which construct a complex chord instead of modeling the chord as one event