2026
Matthew Peachey
Investigating Continuous Interactions for generative Tools in the Context of Musical Creativity PhD Thesis
Dalhousie University, 2026.
Abstract | BibTeX | Tags: continuous interaction, continuous-interaction-and-machine-learning, control mapping, creativity support tools, digital musical instruments, machine learning, music, sound & music computing
@phdthesis{Peachey2026b,
title = {Investigating Continuous Interactions for generative Tools in the Context of Musical Creativity},
author = {Matthew Peachey},
year = {2026},
date = {2026-10-19},
urldate = {2026-10-19},
school = {Dalhousie University},
abstract = {This thesis investigates continuous interaction as a design principle for Artificial Intelligence (AI)-powered music creativity support tools. Discrete text prompting, the de facto standard for current generative AI systems, can limit musicians’ sense of artistic agency and creative ownership. Continuous interaction instead can enable fine-grained, real-time control over the generative process, helping musicians retain a sense of authorship over the generated output.
This thesis presents three studies that together examine how continuous interaction, integrated into real-time interfaces, can better support musicians’ creative workflows. First, I derived low-dimensional latent representations from a Variational Autoencoder with an intentionally small latent space, integrated them into a real-time GUI, and evaluated them in a mixed-methods study with both novice and experienced synthesizer users (n = 18). Second, I interviewed experienced musicians (n = 10) about their hesitations toward generative AI; their concerns centered on a lack of compelling tools and workflows, further motivating continuous interaction as a design preference. Finally, I developed a framework for Aging Digital Musical Instruments (AgingDMIs), a novel class of instruments that adapt to a user’s play style over time. I then implemented a hardware prototype instantiating one point in the AgingDMI design space, and evaluated it longitudinally with experienced musicians (n= 4) for twelve recurring sessions over several weeks.
The findings presented in this thesis suggest that integrating continuous interaction into generative AI-powered creativity support tools increases musicians’ artistic agency and creative ownership and fits better within their existing creative workflows. I further contribute a validated
design framework for AgingDMIs, a novel class of adaptive and personalized digital musical instruments, and a hardware prototype that together demonstrate the principles of that framework in practice.},
keywords = {continuous interaction, continuous-interaction-and-machine-learning, control mapping, creativity support tools, digital musical instruments, machine learning, music, sound & music computing},
pubstate = {published},
tppubtype = {phdthesis}
}
This thesis investigates continuous interaction as a design principle for Artificial Intelligence (AI)-powered music creativity support tools. Discrete text prompting, the de facto standard for current generative AI systems, can limit musicians’ sense of artistic agency and creative ownership. Continuous interaction instead can enable fine-grained, real-time control over the generative process, helping musicians retain a sense of authorship over the generated output.
This thesis presents three studies that together examine how continuous interaction, integrated into real-time interfaces, can better support musicians’ creative workflows. First, I derived low-dimensional latent representations from a Variational Autoencoder with an intentionally small latent space, integrated them into a real-time GUI, and evaluated them in a mixed-methods study with both novice and experienced synthesizer users (n = 18). Second, I interviewed experienced musicians (n = 10) about their hesitations toward generative AI; their concerns centered on a lack of compelling tools and workflows, further motivating continuous interaction as a design preference. Finally, I developed a framework for Aging Digital Musical Instruments (AgingDMIs), a novel class of instruments that adapt to a user’s play style over time. I then implemented a hardware prototype instantiating one point in the AgingDMI design space, and evaluated it longitudinally with experienced musicians (n= 4) for twelve recurring sessions over several weeks.
The findings presented in this thesis suggest that integrating continuous interaction into generative AI-powered creativity support tools increases musicians’ artistic agency and creative ownership and fits better within their existing creative workflows. I further contribute a validated
design framework for AgingDMIs, a novel class of adaptive and personalized digital musical instruments, and a hardware prototype that together demonstrate the principles of that framework in practice.
This thesis presents three studies that together examine how continuous interaction, integrated into real-time interfaces, can better support musicians’ creative workflows. First, I derived low-dimensional latent representations from a Variational Autoencoder with an intentionally small latent space, integrated them into a real-time GUI, and evaluated them in a mixed-methods study with both novice and experienced synthesizer users (n = 18). Second, I interviewed experienced musicians (n = 10) about their hesitations toward generative AI; their concerns centered on a lack of compelling tools and workflows, further motivating continuous interaction as a design preference. Finally, I developed a framework for Aging Digital Musical Instruments (AgingDMIs), a novel class of instruments that adapt to a user’s play style over time. I then implemented a hardware prototype instantiating one point in the AgingDMI design space, and evaluated it longitudinally with experienced musicians (n= 4) for twelve recurring sessions over several weeks.
The findings presented in this thesis suggest that integrating continuous interaction into generative AI-powered creativity support tools increases musicians’ artistic agency and creative ownership and fits better within their existing creative workflows. I further contribute a validated
design framework for AgingDMIs, a novel class of adaptive and personalized digital musical instruments, and a hardware prototype that together demonstrate the principles of that framework in practice.
Malaika Pandit
Whiskers: A Descriptive Study of Children's Engagement with an Interactive Textured Book Masters Thesis
Dalhousie Univerity, 2026.
Abstract | BibTeX | Tags: book, child-computer interaction, sound & music computing, tangible interfaces, touch
@mastersthesis{Pandit2026,
title = {Whiskers: A Descriptive Study of Children's Engagement with an Interactive Textured Book},
author = {Malaika Pandit},
year = {2026},
date = {2026-08-31},
urldate = {2026-08-31},
school = {Dalhousie Univerity},
abstract = {Electronically augmented children’s books have existed for over two decades, and
commonly respond with a discrete event: a touch selects a pre-authored sound, which
plays to its end regardless of what the hand does next. This thesis asks what such a
book would be like if sound instead followed the hand continuously. An interactive
textured book was built with a fur-covered page over a pressure-sensitive sensor and
two audio engines sharing one contact stream: one synthesizing sound continuously
from the position and movement of an ongoing touch, the other triggering a discrete
recorded sound at touch-down. Eight children aged four to six met both versions in
counterbalanced order, with no task imposed. Every child spent a greater share of
the session in contact under continuous feedback; smiling was coded more often under
discrete feedback for six of eight. Neither is concluded better. What sustained a child
and what delighted one proved to be different measures.},
keywords = {book, child-computer interaction, sound & music computing, tangible interfaces, touch},
pubstate = {published},
tppubtype = {mastersthesis}
}
Electronically augmented children’s books have existed for over two decades, and
commonly respond with a discrete event: a touch selects a pre-authored sound, which
plays to its end regardless of what the hand does next. This thesis asks what such a
book would be like if sound instead followed the hand continuously. An interactive
textured book was built with a fur-covered page over a pressure-sensitive sensor and
two audio engines sharing one contact stream: one synthesizing sound continuously
from the position and movement of an ongoing touch, the other triggering a discrete
recorded sound at touch-down. Eight children aged four to six met both versions in
counterbalanced order, with no task imposed. Every child spent a greater share of
the session in contact under continuous feedback; smiling was coded more often under
discrete feedback for six of eight. Neither is concluded better. What sustained a child
and what delighted one proved to be different measures.
commonly respond with a discrete event: a touch selects a pre-authored sound, which
plays to its end regardless of what the hand does next. This thesis asks what such a
book would be like if sound instead followed the hand continuously. An interactive
textured book was built with a fur-covered page over a pressure-sensitive sensor and
two audio engines sharing one contact stream: one synthesizing sound continuously
from the position and movement of an ongoing touch, the other triggering a discrete
recorded sound at touch-down. Eight children aged four to six met both versions in
counterbalanced order, with no task imposed. Every child spent a greater share of
the session in contact under continuous feedback; smiling was coded more often under
discrete feedback for six of eight. Neither is concluded better. What sustained a child
and what delighted one proved to be different measures.