  Automatic musical accompaniment is where a human musician is accompanied by a
computer musician. The computer musician is able to produce musical
accompaniment that relates musically to the human performance. The
accompaniment should follow the performance using observations of the notes
they are playing. This paper describes a complete and detailed construction of
a score following and accompanying system using Hidden Markov Models (HMMs). It
details how to train a score HMM, how to deal with polyphonic input, how this
HMM work when following score, how to build up a musical accompanist. It
proposes a new parallel hidden Markov model for score following and a fast
decoding algorithm to deal with performance errors.
