Exploiting structural relationships in audio music signals using Markov Logic Networks

We propose an innovative approach for music description at several time-scales in a single unified formalism. More specifically, chord information at the analysis-frame level and global semantic structure are integrated in an elegant and flexible model. Using Markov Logic Networks (MLNs) low-level signal features are encoded with high-level information expressed by logical rules, without the need of a transcription step. Our results demonstrate the potential of MLNs for music analysis as they can express both structured relational knowledge through logic as well as uncertainty through probabilities.