Abstract
Melodic harmonisation deals with the assignment of harmony (chords) over a given melody. Probabilistic approaches to melodic harmonisation utilise statistical information derived from a training dataset to harmonise a melody. This paper proposes a probabilistic approach for the automatic generation of voice leading for the bass note on a set of given chords from different musical idioms; the chord sequences are assumed to be generated by another system. The proposed bass voice leading (BVL) probabilistic model is part of ongoing work, it is based on the hidden Markov model (HMM) and it determines the bass voice contour by observing the contour of the melodic line. The experimental results demonstrate that the proposed BVL method indeed efficiently captures (in a statistical sense) the characteristic BVL features of the examined musical idioms.
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Acknowledgements
This work is founded by the COINVENT project. The project COINVENT acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET-Open grant number: 611553.
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Makris, D., Kaliakatsos-Papakostas, M., Cambouropoulos, E. (2015). A Probabilistic Approach to Determining Bass Voice Leading in Melodic Harmonisation. In: Collins, T., Meredith, D., Volk, A. (eds) Mathematics and Computation in Music. MCM 2015. Lecture Notes in Computer Science(), vol 9110. Springer, Cham. https://doi.org/10.1007/978-3-319-20603-5_13
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DOI: https://doi.org/10.1007/978-3-319-20603-5_13
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