A dynamic emotion feedback system for music using audio, symbolic, and physiological features

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This project builds on the accomplishments of a long-standing collaboration between WaveDNA, a music software development company in Toronto, and the SMART lab at Ryerson University. The project will focus on developing an emotion feedback system in a music composition and production workflow. Music composers, professional and amateur have specific emotional goals in mind during music creation. Additionally, they would be keen to know about the potential emotion appraisals made by listeners, while listening to their compositions. Despite the widespread use of digital audio workstations in the music production community, there currently exists no commercial software that provides emotion feedback to composers. The dynamic emotion feedback system proposed in this project, would not only benefit the composition process but would also strongly align WaveDNA with the trend in consumer products towards performance feedback through computational analytics. From a research standpoint, although several studies have made advances in predicting emotion judgments of a "general listener" based on information from the music and audio characteristics, emotion prediction remains elusive because of its subjective nature. Preliminary work in the SMART lab has showed that physiological responses are powerful indicators of a listener's emotional state and may be used to model the listener's emotional responses to music. Given the lab's extensive experience in the area of music, emotion, and physiology, through this collaboration, we aim to (1) further current understanding of emotional response to music by developing and validating computational models using machine learning methods; (2) translate validated models into systems appropriate for practical use; and (3) integrate these emotion prediction models into WaveDNA's software suite.