Transcribing Frequency Modulated Musical Expressions from Polyphonic Music Using HMM Constrained Shift Invariant PLCA

In recent years, there has been a lot of work in transcribing polyphonic music using non-negative spectrogram factorization. However, most of them focus on transcribing audio signal into the occurrence of notes, onset and pitch of notes. In this paper, a concept for automatic transcription of frequency modulated musical expressions such as vibrato, glissando is proposed. To transcribe those musical expressions from polyphonic music signal, hidden Markov model constrained shift-invariant probabilistic latent component analysis is used. From a impulse distribution which reveals the frequency variation of each note, each expression can be modelled in accordance with designed rules. Experiments showed that the impulse distribution can be used to transcribe expressions from polyphonic music signals.