Multichannel audiovisual composition using audiovisual sampling, synchronous granular synthesis andpseudorandom number generator algorithms

Over the last century, researchers and artists have developed and employed a range of techniques to create audio visual compositions. From the hand-painted abstract visual music animations by Futuristartists Arnaldo Ginna and Bruno Corra from 1910 to contemporary digital creations based on intricate mathematical algorithms, artists have explored the complex relationship between sonic and visual material using all the tools at their disposal. Some of these techniques are based on the concept of audio visual sampling. Snippets of footage –including both audio and visual components – are cut, manipulated and integrated into an audio visual product in order to generate a new piece of artwork. This research project describes and implements a new method for creating multichannel audio visual compositions based on audio visual sampling, synchronous granular synthesis techniques and pseudorandom number generator algorithms. The project begins by introducing and analysing the concept of audio visual grain within the framework of audio visual sampling. It then elaborates upon a method for multichannel audio visual composition, based on the aforementioned concepts, called MAVASP. Finally, the MAVASP method is implemented in the form of a compositional software environment. There follows a practical approach to using the MAVASP method and software, following a series of creative goals that focus on exploiting the unique characteristics of this audio visual compositional approach to generate original and artistic works. The successful employment of this approach led to the generation of the six pieces that make up the project's portfolio, and prove the validity of this compositional method for creating original and artisticaudiovisual works.

Name dc:type.qualificationname

PhD

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

De Montfort University

Year dc:date.issued

2020

Author dc:creator

• Marti Perez, Francisco

Licence

• https://dora.dmu.ac.uk/bitstreams/56e13884-f1c8-4d83-8552-88c9fde16a08/download