The SIMAC project addresses the study and development of innovative components for a music information retrieval system. The key feature is the usage and exploitation of semantic descriptors of musical content that are automatically extracted from music audio files. These descriptors are generated in two ways as derivations and combinations of lower-level descriptors and as generalizations induced from manually annotated databases by the intensive application of machine learning. The project aims also towards the empowering (i.e. adding value, improving effectiveness) of music consumption behaviours, especially of those that are guided by the concept of similarity.

The reported research has been funded by the EU-FP6-IST- 507142 project SIMAC (Semantic Interaction with Music Audio Contents).