Comparing Three Data Representations for Music with a Sequence-to-Sequence Model
The choices of neural network model and data representation, a mapping between musical notation and input signals for a neural network, have emerged as a major challenge in creating convincing models for melody generation. Music generation can inspire cre
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Marcus Gallagher Nour Moustafa Erandi Lakshika (Eds.)
AI 2020: Advances in Artificial Intelligence 33rd Australasian Joint Conference, AI 2020 Canberra, ACT, Australia, November 29–30, 2020 Proceedings
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Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this subseries at http://www.springer.com/series/1244
Marcus Gallagher Nour Moustafa Erandi Lakshika (Eds.) •
•
AI 2020: Advances in Artificial Intelligence 33rd Australasian Joint Conference, AI 2020 Canberra, ACT, Australia, November 29–30, 2020 Proceedings
123
Editors Marcus Gallagher School of Information Technology and Electrical Engineering University of Queensland Brisbane, QLD, Australia
Nour Moustafa School of Engineering and Information Technology University of New South Wales Canberra, ACT, Australia
Erandi Lakshika School of Engineering and Information Technology University of New South Wales Canberra, ACT, Australia
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-64983-8 ISBN 978-3-030-64984-5 (eBook) https://doi.org/10.1007/978-3-030-64984-5 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This volume contains the papers presented at the 33rd Australasian Joint Conference on Artificial Intelligence (AI 2020). Due to the COVID-19 global pandemic,
