All Outputs (3)

Was that me?: Exploring the effects of error in gestural digital musical instruments (2020)
Presentation / Conference Contribution

Traditional Western musical instruments have evolved to be robust and predictable, responding consistently to the same player actions with the same musical response. Consequently, errors occurring in a performance scenario are typically attributed to... Read More about Was that me?: Exploring the effects of error in gestural digital musical instruments.

Crowd-driven music: Interactive and generative approaches using machine vision and Manhattan (2020)
Presentation / Conference Contribution

This paper details technologies and artistic approaches to crowd-driven music, discussed in the context of a live public installation in which activity in a public space (e.g. a busy railway platform) is used to drive the automated composition and pe... Read More about Crowd-driven music: Interactive and generative approaches using machine vision and Manhattan.

Composing computer generated music, an observational study using IGME: the Interactive Generative Music Environment (2020)
Presentation / Conference Contribution

Computer composed music remains a novel and challenging problem to solve. Despite an abundance of techniques and systems little research has explored how these might be useful for end-users looking to compose with generative and algorithmic music tec... Read More about Composing computer generated music, an observational study using IGME: the Interactive Generative Music Environment.