This paper describes the application of the Effective Boltzmann Machine (EBM) to musical style recognition. After it has been trained with examples of four-part chorales, the EBM is able to distinguish different styles of chorales in unseen pieces of music. Our earlier studies showed that the EBM has many desirable properties. In particular, it is able to complete arbitrary length contextual sequences from learned local context, and synthesise musical harmony for polyphonic music. ln this paper we show that the EBM is able to distinguish chorales from the Baroque period from Norwegian chorales. In summary, the EBM is able to distinguish, firstly, between chorales present in the training set and those that are not. Secondly, the EBM is also able to distinguish chorales of different styles, where one style was used in the training set. We also show that two different EBMs (one trained from examples from Choralbuch and the other trained from Norwegian chorales) are able to distinguish between two different harmonised styles of the same chorale melody. The EBMX system is a PC-based graphical interface, interactive system implementing the EBM for recognition and harmonisation of short musical pieces
