ARTIFICIAL LIFE IN INTEGRATED INTERACTIVE SONIFICATION AND VISUALISATION: INITIAL EXPERIMENTS WITH A PYTHON-BASED WORKFLOW
Author(s)
Armitage, Jack
Crozzoli, Miguel
Jones, Daniel
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Abstract
Multimodal displays that combine interaction, sonification, visualisation
and perhaps other modalities, are seeing increased interest
from researchers seeking to take advantage of cross-modal
perception, by increasing display bandwidth and expanding affordances.
To support researchers and designers, many new tools are
being proposed that aim to consolidate these broad feature sets
into Python libraries, due to Python’s extensive ecosystem that in
particular encompasses the domain of artificial intelligence (AI).
Artificial life (ALife) is a domain of AI that is seeing renewed
interest, and in this work we share initial experiments exploring
its potential in interactive sonification, through the combination of
two new Python libraries, Tölvera and SignalFlow. Tölvera is a library
for composing self-organising systems, with integrated open
sound control, interactive machine learning, and computer vision,
and SignalFlow is a sound synthesis framework that enables realtime
interaction with an audio signal processing graph via standard
Python syntax and data types. We demonstrate how these two tools
integrate, and the first author reports on usage in creative coding
and artistic performance. So far we have found it useful to consider
ALife as affording synthetic behaviour as a display modality,
making use of human perception of complex, collective and emergent
dynamics. In addition, we think ALife also implies a broader
perspective on interaction in multimodal display, blurring the lines
between data, agent and observer. Based on our experiences, we
offer possible future research directions for tool designers and researchers.
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Date
2024-06
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Creative Commons Attribution Non-Commercial 4.0 International (CC BY-NC 4.0)