Melody harmonisation with interpolated probabilistic models

International audienceMost melody harmonisation systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric struc- ture, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation. We evaluate our models in terms of their cross-entropy and their performance in harmonisation experiments. The proposed model o ered higher chord root accuracy than the reference musicological rule-based harmoniser by up to 5% absolute