Improved Automatic Instrumentation Role Classification and Loop Activation Transcription

Drysdale, Jake and Hockman, Jason and Ramires, Antonio and Serra, Xavier (2022) Improved Automatic Instrumentation Role Classification and Loop Activation Transcription. In: Digital Audio Effects, 6th - 10th October 2022, Vienna, Austria.

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Abstract

Many electronic music (EM) genres are composed through the activation of short audio recordings of instruments designed for seamless repetition—or loops. In this work, loops of key structural groups such as bass, percussive or melodic elements are labelled by the role they occupy in a piece of music through the task of automatic instrumentation role classification (AIRC). Such labels assist EM producers in the identification of compatible loops in large unstructured audio databases. While human annotation is often laborious, automatic classification allows for fast and scalable generation of these labels. We experiment with several deeplearning architectures and propose a data augmentation method for improving multi-label representation to balance classes within the Freesound Loop Dataset. To improve the classification accuracy of the architectures, we also evaluate different pooling operations. Results indicate that in combination with the data augmentation and pooling strategies, the proposed system achieves state-of-theart performance for AIRC. Additionally, we demonstrate how our proposed AIRC method is useful for analysing the structure of EM compositions through loop activation transcription.

Item Type:	Conference or Workshop Item (Paper)
Dates:	Date Event 1 July 2022 Accepted 6 October 2022 Published Online
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-04 - software engineering CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence CAH25 - design, and creative and performing arts > CAH25-02 - performing arts > CAH25-02-02 - music
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Jason Hockman
Date Deposited:	06 Dec 2022 16:43
Last Modified:	22 Mar 2023 12:00
URI:	https://www.open-access.bcu.ac.uk/id/eprint/13984

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