Chorale harmonization: A view from a search control perspective

Chorale harmonization is one of the most popular problem domains for AI-music researchers. The problem has been approached with various techniques ranging from a knowledge intensive approach on one end to a data intensive approach on the other end. Various approaches offer different strengths and pose different weaknesses. In this report, we explain our knowledge intensive approach. Here, we view chorale harmonization from a search control perspective. In this perspective, the harmonization activities are discretely captured as states. These states form a state space, which cannot be exhaustively examined since it is intractable by nature. To overcome the intractability problem, we propose a careful knowledge engineering approach. The approach offers a useful language specialized for the chorale harmonization task. This language controls the search at the meta-level through its three primitives, namely: rules, tests and measures. The harmonization outputs obtained from this method are very promising. The approach also offers a very promising application in the AI-education area.