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Electric Guitar Sound Restoration with Diffusion Models

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Mo, Ronald K. (2023) Electric Guitar Sound Restoration with Diffusion Models. In: DMRN+18: Digital Music Research Network One-day Workshop 2023, 19 Dec 2023, Queen Mary University of London, London, UK. (Unpublished)

Item Type: Conference or Workshop Item (Speech)

Abstract

This work aims to investigate the potential of employing Denoising diffusion probabilistic models, commonly referred to as diffusion models, to revert a processed electric guitar recording to its original, unaltered form while retaining all the expressive elements of the performance such as dynamics and articulation. Specifically, a parallel dataset is constructed, containing both the unprocessed and processed versions of the guitar recordings, which is used for training a diffusion model. To preserve the expressiveness, the model is conditioned on the processed guitar recording when restoring the raw guitar sound. This research has the potential to enhance the accuracy of various music information retrieval tasks, such as automatic
music transcription.

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More Information

Depositing User: Ronald Mo

Identifiers

Item ID: 17200
URI: http://sure.sunderland.ac.uk/id/eprint/17200
Official URL: https://www.qmul.ac.uk/dmrn/dmrn18/

Users with ORCIDS

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

Catalogue record

Date Deposited: 09 Jan 2024 09:17
Last Modified: 09 Jan 2024 09:30

Contributors

Author: Ronald K. Mo ORCID iD

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing > Artificial Intelligence
Performing Arts > Music

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