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In a Silent Way: Communication between AI and improvising musicians beyond sound

McCormack, Jon; Gifford, Toby; Hutchings, Patrick; Llano, Maria Teresa; Yee-King, Matthew and d'Inverno, Mark. 2019. 'In a Silent Way: Communication between AI and improvising musicians beyond sound'. In: CHI 2019 Conference on Human Factors in Computing Systems. Glasgow, United Kingdom 4-9 May 2019. [Conference or Workshop Item]

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Abstract or Description

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.

Item Type:

Conference or Workshop Item (Paper)

Identification Number (DOI):

https://doi.org/10.1145/3290605.3300268

Keywords:

AI Systems, Improvisation, Extra-musical Communication

Related URLs:

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
15 December 2018Accepted
4 May 2019Published

Event Location:

Glasgow, United Kingdom

Date range:

4-9 May 2019

Item ID:

25500

Date Deposited:

09 Jan 2019 13:19

Last Modified:

17 Jun 2019 14:02

URI:

http://research.gold.ac.uk/id/eprint/25500

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