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Emotion-driven Motivic Development using Diffusion Models

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Mo, Ronald K. (2023) Emotion-driven Motivic Development using Diffusion Models. In: CHIME Annual One-day Music and HCI Workshop, 04 Dec 2023, The Open University, Milton Keynes, UK.

Item Type: Conference or Workshop Item (Speech)

Abstract

Denoising diffusion probabilistic models, or diffusion models, have been successfully used for generating images, audio, and music. This work aims to investigate the potential of employing diffusion models to develop a motif composed by human composers to arouse specific emotions. To achieve this, a dataset consisting of melodies and their corresponding emotion label is constructed for training the diffusion model. The model is conditioned on the user-generated motif and a label displaying the desired emotion category, which opens up an opportunity for human composers to collaborate with computer technology in the field of music composition.

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Depositing User: Ronald Mo

Identifiers

Item ID: 17102
URI: http://sure.sunderland.ac.uk/id/eprint/17102
Official URL: https://www.chime.ac.uk/chime-annual-workshop

Users with ORCIDS

ORCID for Ronald K. Mo: ORCID iD orcid.org/0000-0002-8746-2069

Catalogue record

Date Deposited: 21 Dec 2023 07:36
Last Modified: 21 Dec 2023 07:36

Contributors

Author: Ronald K. Mo ORCID iD

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing > Artificial Intelligence
Computing > Human-Computer Interaction
Performing Arts > Music

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