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Summary:

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Table of Contents:

• Intro
• Preface
• Organization
• Contents
• Long Talks
• SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms
• 1 Introduction
• 2 Related Work
• 3 Methodology and System Overview
• 4 Experimental Study
• 4.1 Experimental Setup
• 4.2 Experimental Analysis
• 5 Conclusion and Future Work
• References
• A Systematic Evaluation of GPT-2-Based Music Generation
• 1 Introduction
• 2 Background
• 2.1 GPT-2 Models
• 2.2 Representing Music Data for GPT-2 Input
• 2.3 Statistical Analysis of Generative Music Models

• 3 Musical Metrics
• 4 Dataset Curation
• 5 Evaluating Generative Model Output
• 5.1 Varying the Training Level
• 5.2 Varying the Training Corpus
• 6 Web Application
• 7 Conclusions and Future Work
• References
• Expressive Aliens
• Laban Effort Factors for Non-anthropomorphic Morphologies
• 1 Introduction
• 2 Background
• 2.1 Movement Qualities
• 2.2 Motion Synthesis
• 2.3 Anthropomorphic versus Non-anthropomorphic Characters
• 2.4 Physical Validity versus Expressivity
• 3 Implementation
• 3.1 Morphologies
• 3.2 SAC Algorithm
• 3.3 Observation Vector
• 3.4 Rewards
• 4 Training
• 5 Results
• 6 Discussion
• 7 Conclusion and Outlook
• References
• Painting with Evolutionary Algorithms
• 1 Introduction
• 2 Rearranging Brush Strokes
• 3 Algorithms
• 4 Experiment and Results
• 5 Extrapolation
• 6 Some Final Remarks
• References
• Evolutionary Construction of Stories that Combine Several Plot Lines
• 1 Introduction
• 2 Related Work
• 2.1 Plot Line Combination
• 2.2 Computational Metrics for Stories
• 2.3 Evolutionary Construction of Narratives
• 3 An Evolutionary Multiplot Story Composer
• 3.1 The Knowledge Resources
• 3.2 Character Fusion and Discourse Planning
• 3.3 Representing Multiplot Stories for Evolutionary Construction
• 3.4 Constructing an Initial Population
• 3.5 Evolutionary Operators
• 3.6 Fitness Functions
• 4 Discussion
• 4.1 Results
• 4.2 Relation with Previous Work
• 5 Conclusions
• References
• Fashion Style Generation: Evolutionary Search with Gaussian Mixture Models in the Latent Space
• 1 Introduction
• 2 Related Work
• 2.1 GANs
• 2.2 Fashion Styles
• 2.3 Evolutionary Search of GANs' Latent Space
• 3 Dataset
• 4 Model
• 4.1 Generative Model
• 4.2 Style Model
• 4.3 Evolutionary Search
• 5 Results
• 6 Discussion
• 7 Conclusion and Future Work
• References
• Classification of Guitar Effects and Extraction of Their Parameter Settings from Instrument Mixes Using Convolutional Neural Networks
• 1 Introduction
• 2 Method and Materials
• 2.1 Dataset for Guitar Effect Parameter Extraction
• 2.2 Dataset for Guitar Effect Classification
• 2.3 Time-Frequency Representations
• 2.4 Convolutional Neural Networks
• 2.5 Training and Evaluation
• 2.6 Baseline
• 2.7 Robustness Analysis
• 3 Results
• 3.1 Effect Classification
• 3.2 Effect Parameter Extraction
• 3.3 Robustness to Noise and Pitch Shifts

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Contributors:

Martins, Tiago , editor

Rodríguez-Fernández, Nereida , editor

Rebelo, Sérgio M. , editor

Meetings:

EvoMUSART (Conference) (11th : 2022 : Madrid, Spain)

EVOSTAR (Conference) (2022 : Madrid, Spain)

Languages:

English

Language Notes:

Item content: English

Main Work:

Artificial intelligence in music, sound, art and design: 11th International Conference, EvoMUSART 2022, held as part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, proceedings [EvoMUSART (Conference)]

Other Related Resources:

Print version: Artificial intelligence in music, sound, art and design [EvoMUSART] (Cham : Springer, 2022 — ISBN 9783031037887; OCLC Number 1308478909)

Related Series:

Lecture notes in computer science; [volume] 13221

Subjects:

Evolutionary programming (Computer science) — Congresses

Artificial intelligence — Congresses

Computer music — Congresses

Computer graphics — Congresses

Artificial intelligence

Computer graphics

Computer music

Evolutionary programming (Computer science)

Genres:

Conference papers and proceedings

General Notes:

Includes author index.
Description based on: Print version record.

Physical Description:

1 online resource (1 volume) : illustrations (black and white).

Digital Characteristics:

text file

Call Numbers:

QA76.618 .A785 2022eb

ISBNs:

9783031037894 (electronic bk.)
3031037898 (electronic bk.)
9783031037887 (print) [Invalid]
303103788X (print) [Invalid]

Other Standard Numbers:

Digital Object Identifier: 10.1007/978-3-031-03789-4

OCLC Numbers:

1311964558