Grant: Collaborative Research and Development Grants

This project represents a natural evolution in the collaboration between waveDNA, a music software development company, and the SMART (Science of Music, Auditory Research and Technology) lab at Ryerson University. WaveDNA's unique focus lies in equipping its software with human intelligence based on empirical research, thereby providing a means of generating meaningful musical variations. This project aims to improve waveDNA's existing musical analysis and generation engines through new behavioural and electrophysiological experiments. Results of these experiments will guide the development of new algorithms in collaboration with waveDNA. Although existing music applications such as digital audio workstations have a great degree of functionality, they do not address the user's cognitive/emotional appraisals through intelligent interaction. We believe that this project will address this void and satisfy a broad base of customers including musicians and researchers. The project will target four specific areas. First, we will improve waveDNA's Rhythm Generator by gathering cognitive appraisals of waveDNA's components, and by integrating these results into the Liquid Loops application in the form of cognitively-based navigation controls. Second, we will run electrophysiological studies to better understand listener perception of fine-grained aspects of rhythmic structure. Results of these studies will help us to further develop the navigation controls. Third, we propose to continue our work on tonal similarity to develop an algorithm for incorporation into waveDNA's future Liquid Harmony application. Finally, we intend to continue our efforts towards a computational model for emotion in music that incorporates rhythmic as well as tonal factors. Commercially, this project will provide a competitive advantage for a suite of cutting-edge music software tools. These tools will incorporate a refined symbolic representation of music (waveDNA IP), systems intelligence drawn from music cognition research, and search methods drawn from music information retrieval.