Towards a Socio-cultural Compatibility of MIR Systems

Future MIR systems will be of great use and pleasure for potential users. If researchers have a clear picture about their “customers” in mind they can aim at building and evaluating their systems exactly inside the different socio-cultural environments of such music listeners. Since music is in most cases embedded into a socio-cultural process we propose especially to evaluate MIR applications outside the lab during daily activities. For this purpose we designed a mobile music recommendation system relying on a trimodal music similarity metric, which allows for subjective on-the-fly adjustments of recommendations. It offers online access to large-scale metadata repositories as well as an audio database containing 1000 songs. We did first smallscale evaluations of this approach and came to interesting results regarding the perception of song similarity concerning the relations between sound, cultural issues and lyrics. Our paper will also give insights to the three different underlying approaches for song similarity computation (sound, cultural issues, lyrics), focusing in detail on a novel clustering of album reviews as found at online music retailers.