In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound

February 18, 2019 Β· Declared Dead Β· πŸ› International Conference on Human Factors in Computing Systems

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Authors Jon McCormack, Toby Gifford, Patrick Hutchings, Maria Teresa Llano Rodriguez, Matthew Yee-King, Mark d'Inverno arXiv ID 1902.06442 Category cs.HC: Human-Computer Interaction Citations 69 Venue International Conference on Human Factors in Computing Systems Last Checked 3 months ago
Abstract
Collaboration is built on trust, and establishing trust with a creative Artificial Intelligence is difficult when the decision process or internal state driving its behaviour isn't exposed. When human musicians improvise together, a number of extra-musical cues are used to augment musical communication and expose mental or emotional states which affect musical decisions and the effectiveness of the collaboration. We developed a collaborative improvising AI drummer that communicates its confidence through an emoticon-based visualisation. The AI was trained on musical performance data, as well as real-time skin conductance, of musicians improvising with professional drummers, exposing both musical and extra-musical cues to inform its generative process. Uni- and bi-directional extra-musical communication with real and false values were tested by experienced improvising musicians. Each condition was evaluated using the FSS-2 questionnaire, as a proxy for musical engagement. The results show a positive correlation between extra-musical communication of machine internal state and human musical engagement.
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