An Artificial Neural Net for Harmonizing Melodies

Whenever a musician needs to harmonize or analyze harmonization of a given melody, after establishing the key, he/she tries to extract, for each measure, some harmonic hint from the melody in the form of key notes. These key notes provide a sparse harmonic outline that will be completed to a full harmony using constraints derived from: the harmonic and the melodic contexts, the musical style and culture and the individual musical taste. Based on this analysis, we propose a Jordan's sequential neural net the structure of which reflects the way the human musician proceeds: it contains a sub-net that identifies key notes. The net is capable to leaxn simple harmonized melodies and generalizing what it has learned by harmonizing melodies it has never seen.