| Popis: |
In this paper, the effectiveness of Conditional Restricted Boltzmann Machines (CRBMs) as universal feature extractors for classifying symbolic music is investigated. An average monophonic classification accuracy of 72% was achieved when discriminating between string quartets movements of Mozart and Haydn. When the decisions of individual monophonic parts were combined using a basic voting scheme, a polyphonic classification accuracy of 96% was achieved, a substantial improvement compared to the best state-of-the-art performance to date of 80%. It was observed that the classification rate depended heavily on the exact composition of training and test set: the classifier performance deteriorated when the time of composition increased between training and test set. This supports the observation that the ”style” of a composer is not a fixed given but varies over time. |
