Knowledge-driven methodologies: Challenges

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Integrate insights from disciplines relevant to MIR and make them useful for our research. This requires mutual understanding and exchange of results and researchers. The challenge is to integrate research agendas through the formulation of common interests and goals as well as a common vocabulary and dedicated communication paths. This will be important for both MIR and all other disciplines caring about music since there is a mutual benefit to be gained from this.

Develop richer musical models incorporating musicological knowledge. MIR has been focusing on a limited number of musical concepts, which are modelled at a shallower depth than they are treated by musicologists. Enriching these concepts will help bridge the gap between low-level MIR representations and higher-level semantic concepts.

Extend and strengthen existing links to music psychology. An example for a joint interest is the clearer formulation and understanding of the notion of "music similarity" with the help of music psychological results and proper experimentation. This requires that music psychologists be informed about MIR models and methods to compute music similarity and that MIR researchers are being educated about how music psychologists access subjective notions and cognitive aspects of music similarity in humans. Expected outcomes are improved models and algorithms to compute music similarity as well as computer aided selection of research stimuli for the psychological experiments.

Give due attention to the social function of music in our research. This makes it necessary that MIR cares about groups of individuals and their interaction instead of about disconnected individuals. Taste formation, preference and music selection are a combined function of personal and group variables, and we currently do not know how to weight both aspects to achieve good predictive models. Research and technologies that help to understand, modify, increase or make possible group cohesion, improvements on self-image, or strengthen collective bonds could have a strong impact, especially on disfavoured, problem-prone and marginal groups. The final challenge here would be to be able to shift the increasing trend of enjoying music as an individual, isolated, activity, making social ways to search, share, listen to, and re-create the otherwise "personal" collections of music possible.

Learn, understand and eventually integrate neuro-scientific results concerning music. The question of how music influences emotions of listeners is a good example which is of great interest to MIR and where a growing body of neuro-scientific results on the basics of emotional experience exists. Comprehension of these results could enable better and richer MIR models of emotion in music. On the other hand, education of neuroscience researchers in MIR technology might help design of brain studies on music (e.g. in producing generative musical research stimuli).