Open Access Te Herenga Waka-Victoria University of Wellington
Browse
Download file
Download file
Download file
Download file
Download file
Download file
Download file
1/1
7 files

Artificial Synaesthesia: An exploration of machine learning image synthesis for soundscape audio visualisation

Download all (2.29 GB)
thesis
posted on 2022-07-31, 23:24 authored by Willcox, Stacey

Within soundscape research, audio visualisations are generally targeted towards scientific audiences and not produced with artistic intentions. Machine learning is utilised in this field to increase efficiency when dealing with large amounts of data, recognizing patterns, and classifying audio. Although machine learning is effective for these purposes, it also offers image synthesis capabilities which have not been taken advantage of in current audio visualisation production. This research aims to answer the question, ‘How might machine learning image synthesis be used to visualise soundscape audio?’.

Through an iterative design process, a design pipeline was developed to generate visualisations of audio using Pix2Pix (Isola, et al., 2016), a conditional adversarial neural network. Through a process of extracting audio features, converting these into simple grid images and feeding them into a trained machine learning model, a new visual interpretation of the audio can be experienced in the form of images and videos. The video design outputs communicate visual change of audio through the interrelated transformation of colour, shape, detail, and size of flower-like figures. These outputs aim to bring attention to the value of soundscapes through visually demonstrating their unique qualities. The method developed has not been previously documented according to the available literature and marks an exciting exploration of the new application of machine learning image-to-image translation as a creative tool for audio visualisation.

History

Copyright Date

2020-01-01

Date of Award

2021-01-01

Publisher

Te Herenga Waka—Victoria University of Wellington

Rights License

Author Retains Copyright

Degree Discipline

Design Innovation

Degree Grantor

Te Herenga Waka—Victoria University of Wellington

Degree Level

Masters

Degree Name

Master of Design Innovation

ANZSRC Type Of Activity code

4 Experimental Development

Victoria University of Wellington Item Type

Awarded Research Masters Thesis

Language

en_NZ

Victoria University of Wellington School

School of Design Innovation

Advisors

Langelaar, Walter; White, Tom