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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 / / edited by Tiago Martins, Nereida Rodríguez-Fernández, and Sérgio M. Rebelo
| 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 / / edited by Tiago Martins, Nereida Rodríguez-Fernández, and Sérgio M. Rebelo |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (427 pages) |
| Disciplina | 700.28563 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer graphics
Computer music Artificial intelligence |
| ISBN | 3-031-03789-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 -- 4 Discussion -- 4.1 Guitar Effect Classification -- 4.2 Guitar Effect Parameter Extraction -- 4.3 Robustness -- 4.4 Limitations -- 5 Conclusion -- References -- Aesthetic Evaluation of Experimental Stimuli Using Spatial Complexity and Kolmogorov Complexity -- 1 Introduction -- 2 Conceptual Model -- 3 Spatial Complexity Measure -- 4 Kolmogorov Complexity of 2D Patterns -- 5 Experiment and Results -- 5.1 Method -- 5.2 Material -- 5.3 Procedure -- 5.4 Results -- 5.5 Procedure for the Extended Study -- 5.6 Results and Analysis -- 6 Discussions -- References -- Towards the Generation of Musical Explanations with GPT-3 -- 1 Introduction -- 2 Background -- 2.1 Communication in Human-Machine Music Interactions -- 2.2 Transformer-Based Approaches in Music. 2.3 Transformer-Based Approaches in Explainable AI -- 3 Musical Capability of GPT-3 -- 3.1 Extracting the Key from a Sequence of Notes -- 3.2 Providing Explanations for a Fictional Song -- 3.3 Extracting Musical Information Using MusicABC Notation -- 4 Explaining Musical Decisions -- 4.1 Methodology -- 4.2 Results -- 5 Discussion -- 6 Conclusion -- References -- Lamuse: Leveraging Artificial Intelligence for Sparking Inspiration -- 1 Introduction -- 2 The Creative Process -- 2.1 Context -- 2.2 General Assumptions and Process -- 2.3 Data Requirements -- 3 The Artificial Intelligence -- 3.1 Artwork Decomposition -- 3.2 Recomposing with a Visual Universe and Projection -- 3.3 Style Transfer -- 4 Results Analysis and Discussion -- 4.1 E. Potier -- 4.2 Rarès-Victor -- 4.3 N. Varoqui -- 4.4 O. Masmonteil -- 5 Conclusion -- References -- EvoDesigner: Towards Aiding Creativity in Graphic Design -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Evolutionary Engine -- 4 Experimental Setup and Results -- 5 Conclusion -- References -- Conditional Drums Generation Using Compound Word Representations -- 1 Introduction -- 2 Related Work -- 3 Data Encoding Representation -- 3.1 Encoder Representation - Conditional Information -- 3.2 Decoder Representation - Generated Drum Sequences -- 4 Proposed Architecture -- 4.1 Encoder - Decoder -- 4.2 Implementation Details -- 5 Experimental Setup -- 5.1 Dataset and Preprocessing -- 5.2 Evaluation Metrics -- 6 Results -- 6.1 Objective Evaluation -- 6.2 Subjective Evaluation -- 7 Conclusions -- References -- Music Style Transfer Using Constant-Q Transform Spectrograms -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 4 Experiments and Results -- 4.1 CycleGAN Hyperparameter Experiment -- 4.2 CQTGAN Sample Rates Experiment -- 4.3 Unseen Audio Examples Experiment -- 5 Survey Evaluation -- 6 Discussion. 7 Conclusions and Future Work -- References -- SpeechTyper: From Speech to Typographic Composition -- 1 Introduction -- 2 Related Work -- 3 SpeechTyper -- 3.1 Extracting Speech Data -- 3.2 Designing Glyphs -- 3.3 Creating Typographic Compositions Based on Speech -- 4 Experimentation -- 4.1 Setup -- 4.2 Results/Discussion -- 5 Conclusion and Future Work -- References -- A Creative Tool for the Musician Combining LSTM and Markov Chains in Max/MSP -- 1 Introduction -- 2 Data Representation -- 2.1 Pitch -- 2.2 Time -- 2.3 MIDI Analyzer -- 3 LSTM Data Encoding -- 3.1 Pitch -- 3.2 Rhythm -- 3.3 Machine Learning Datasets -- 4 Scramble -- 5 User Interface -- 6 Experimental Results -- 7 Conclusions and Future Work -- References -- Translating Emotions from EEG to Visual Arts -- 1 Introduction -- 2 Background and Related Works -- 3 Preparation of Datasets -- 4 Pipeline -- 4.1 Extra Losses -- 5 Experiments and Results -- 5.1 Example Experiment -- 6 Results Assessment: Online Survey -- 7 Discussion -- 8 Conclusions -- References -- Emotion-Driven Interactive Storytelling: Let Me Tell You How to Feel -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Emotion Recognition -- 3.2 Interface Design -- 3.3 System's Assessment -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts -- 1 Introduction -- 2 Background -- 3 Modern Evolution Strategies for Creativity -- 4 Fitting Concrete Target Image -- 5 Fitting Abstract Concept with CLIP -- 6 Discussion and Conclusion -- References -- Co-creative Product Design with Interactive Evolutionary Algorithms: A Practice-Based Reflection -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 Design Study -- 4.1 Design Task -- 4.2 Study Method -- 4.3 Participant: The Designer -- 4.4 Software Tools and Algorithm. 4.5 Findings: Introspective Design Reflections -- 5 Discussion -- 5.1 Early Constraining of the Design Space -- 5.2 Support in Problem-Solution Co-evolution -- 5.3 Escaping and Falling in a Fixation Trap -- 5.4 The IGA as Creative Partner -- 5.5 Study Limitations -- 6 Conclusion and Future Work -- References -- Sound Model Factory: An Integrated System Architecture for Generative Audio Modelling -- 1 Background and Motivation -- 1.1 Previous Work -- 2 Architecture -- 2.1 System Overview -- 2.2 System Components -- 3 Connecting the GAN and the RNN -- 3.1 Parameter Linearization -- 4 Evaluation -- 4.1 Human Evaluation Adaptively Smoothed Latent Space -- 4.2 Parameter Response Time -- 4.3 Sound Quality Evaluation Based on Audio Classification -- 4.4 Continuous Interpolation of Pitch and Timbre -- 5 Conclusion -- References -- Short Talks -- An Application of Neural Embedding Models for Representing Artistic Periods -- 1 Introduction -- 2 Data -- 3 Methodology -- 3.1 word2vec -- 3.2 t-SNE -- 4 Results -- 4.1 Salvador Dalí -- 4.2 Vincent van Gogh -- 4.3 Pablo Picasso -- 5 Discussion -- 6 Conclusion -- References -- MusIAC: An Extensible Generative Framework for Music Infilling Applications with Multi-level Control -- 1 Introduction -- 2 Related Work -- 3 Proposed Model and Representation -- 3.1 Adding Control Features -- 3.2 Data Representation -- 3.3 Model Architecture -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Model Configuration and Training -- 4.3 Inference Strategy -- 5 Evaluation -- 5.1 Objective Evaluation Using Selected Metrics -- 5.2 The Interactive Interface and Controllability -- 6 Conclusion -- References -- A Study on Noise, Complexity, and Audio Aesthetics -- 1 Introduction -- 2 Conceptual over Perceptual -- 2.1 Japanoise -- 3 Complexity -- 3.1 Complexity and Computational Aesthetics -- 4 Proposed Aesthetic Metrics -- 5 Experiment. 6 Discussion. |
| Record Nr. | UNISA-996472070203316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
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 / / edited by Tiago Martins, Nereida Rodríguez-Fernández, and Sérgio M. Rebelo
| 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 / / edited by Tiago Martins, Nereida Rodríguez-Fernández, and Sérgio M. Rebelo |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (427 pages) |
| Disciplina | 700.28563 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer graphics
Computer music Artificial intelligence |
| ISBN | 3-031-03789-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 -- 4 Discussion -- 4.1 Guitar Effect Classification -- 4.2 Guitar Effect Parameter Extraction -- 4.3 Robustness -- 4.4 Limitations -- 5 Conclusion -- References -- Aesthetic Evaluation of Experimental Stimuli Using Spatial Complexity and Kolmogorov Complexity -- 1 Introduction -- 2 Conceptual Model -- 3 Spatial Complexity Measure -- 4 Kolmogorov Complexity of 2D Patterns -- 5 Experiment and Results -- 5.1 Method -- 5.2 Material -- 5.3 Procedure -- 5.4 Results -- 5.5 Procedure for the Extended Study -- 5.6 Results and Analysis -- 6 Discussions -- References -- Towards the Generation of Musical Explanations with GPT-3 -- 1 Introduction -- 2 Background -- 2.1 Communication in Human-Machine Music Interactions -- 2.2 Transformer-Based Approaches in Music. 2.3 Transformer-Based Approaches in Explainable AI -- 3 Musical Capability of GPT-3 -- 3.1 Extracting the Key from a Sequence of Notes -- 3.2 Providing Explanations for a Fictional Song -- 3.3 Extracting Musical Information Using MusicABC Notation -- 4 Explaining Musical Decisions -- 4.1 Methodology -- 4.2 Results -- 5 Discussion -- 6 Conclusion -- References -- Lamuse: Leveraging Artificial Intelligence for Sparking Inspiration -- 1 Introduction -- 2 The Creative Process -- 2.1 Context -- 2.2 General Assumptions and Process -- 2.3 Data Requirements -- 3 The Artificial Intelligence -- 3.1 Artwork Decomposition -- 3.2 Recomposing with a Visual Universe and Projection -- 3.3 Style Transfer -- 4 Results Analysis and Discussion -- 4.1 E. Potier -- 4.2 Rarès-Victor -- 4.3 N. Varoqui -- 4.4 O. Masmonteil -- 5 Conclusion -- References -- EvoDesigner: Towards Aiding Creativity in Graphic Design -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Evolutionary Engine -- 4 Experimental Setup and Results -- 5 Conclusion -- References -- Conditional Drums Generation Using Compound Word Representations -- 1 Introduction -- 2 Related Work -- 3 Data Encoding Representation -- 3.1 Encoder Representation - Conditional Information -- 3.2 Decoder Representation - Generated Drum Sequences -- 4 Proposed Architecture -- 4.1 Encoder - Decoder -- 4.2 Implementation Details -- 5 Experimental Setup -- 5.1 Dataset and Preprocessing -- 5.2 Evaluation Metrics -- 6 Results -- 6.1 Objective Evaluation -- 6.2 Subjective Evaluation -- 7 Conclusions -- References -- Music Style Transfer Using Constant-Q Transform Spectrograms -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 4 Experiments and Results -- 4.1 CycleGAN Hyperparameter Experiment -- 4.2 CQTGAN Sample Rates Experiment -- 4.3 Unseen Audio Examples Experiment -- 5 Survey Evaluation -- 6 Discussion. 7 Conclusions and Future Work -- References -- SpeechTyper: From Speech to Typographic Composition -- 1 Introduction -- 2 Related Work -- 3 SpeechTyper -- 3.1 Extracting Speech Data -- 3.2 Designing Glyphs -- 3.3 Creating Typographic Compositions Based on Speech -- 4 Experimentation -- 4.1 Setup -- 4.2 Results/Discussion -- 5 Conclusion and Future Work -- References -- A Creative Tool for the Musician Combining LSTM and Markov Chains in Max/MSP -- 1 Introduction -- 2 Data Representation -- 2.1 Pitch -- 2.2 Time -- 2.3 MIDI Analyzer -- 3 LSTM Data Encoding -- 3.1 Pitch -- 3.2 Rhythm -- 3.3 Machine Learning Datasets -- 4 Scramble -- 5 User Interface -- 6 Experimental Results -- 7 Conclusions and Future Work -- References -- Translating Emotions from EEG to Visual Arts -- 1 Introduction -- 2 Background and Related Works -- 3 Preparation of Datasets -- 4 Pipeline -- 4.1 Extra Losses -- 5 Experiments and Results -- 5.1 Example Experiment -- 6 Results Assessment: Online Survey -- 7 Discussion -- 8 Conclusions -- References -- Emotion-Driven Interactive Storytelling: Let Me Tell You How to Feel -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Emotion Recognition -- 3.2 Interface Design -- 3.3 System's Assessment -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts -- 1 Introduction -- 2 Background -- 3 Modern Evolution Strategies for Creativity -- 4 Fitting Concrete Target Image -- 5 Fitting Abstract Concept with CLIP -- 6 Discussion and Conclusion -- References -- Co-creative Product Design with Interactive Evolutionary Algorithms: A Practice-Based Reflection -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 Design Study -- 4.1 Design Task -- 4.2 Study Method -- 4.3 Participant: The Designer -- 4.4 Software Tools and Algorithm. 4.5 Findings: Introspective Design Reflections -- 5 Discussion -- 5.1 Early Constraining of the Design Space -- 5.2 Support in Problem-Solution Co-evolution -- 5.3 Escaping and Falling in a Fixation Trap -- 5.4 The IGA as Creative Partner -- 5.5 Study Limitations -- 6 Conclusion and Future Work -- References -- Sound Model Factory: An Integrated System Architecture for Generative Audio Modelling -- 1 Background and Motivation -- 1.1 Previous Work -- 2 Architecture -- 2.1 System Overview -- 2.2 System Components -- 3 Connecting the GAN and the RNN -- 3.1 Parameter Linearization -- 4 Evaluation -- 4.1 Human Evaluation Adaptively Smoothed Latent Space -- 4.2 Parameter Response Time -- 4.3 Sound Quality Evaluation Based on Audio Classification -- 4.4 Continuous Interpolation of Pitch and Timbre -- 5 Conclusion -- References -- Short Talks -- An Application of Neural Embedding Models for Representing Artistic Periods -- 1 Introduction -- 2 Data -- 3 Methodology -- 3.1 word2vec -- 3.2 t-SNE -- 4 Results -- 4.1 Salvador Dalí -- 4.2 Vincent van Gogh -- 4.3 Pablo Picasso -- 5 Discussion -- 6 Conclusion -- References -- MusIAC: An Extensible Generative Framework for Music Infilling Applications with Multi-level Control -- 1 Introduction -- 2 Related Work -- 3 Proposed Model and Representation -- 3.1 Adding Control Features -- 3.2 Data Representation -- 3.3 Model Architecture -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Model Configuration and Training -- 4.3 Inference Strategy -- 5 Evaluation -- 5.1 Objective Evaluation Using Selected Metrics -- 5.2 The Interactive Interface and Controllability -- 6 Conclusion -- References -- A Study on Noise, Complexity, and Audio Aesthetics -- 1 Introduction -- 2 Conceptual over Perceptual -- 2.1 Japanoise -- 3 Complexity -- 3.1 Complexity and Computational Aesthetics -- 4 Proposed Aesthetic Metrics -- 5 Experiment. 6 Discussion. |
| Record Nr. | UNINA-9910561297303321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández
| Artificial Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (501 pages) : illustrations |
| Disciplina | 005.11 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Education—Data processing Machine learning Image processing—Digital techniques Computer vision Artificial intelligence Software engineering Theory of Computation Computers and Education Machine Learning Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Software Engineering |
| ISBN | 3-030-72914-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Sculpture Inspired Musical Composition, One Possible Approach -- Network Bending: Expressive Manipulation of Deep Generative Models -- SyVMO: Synchronous Variable Markov Oracle for Modeling and Predicting Multi-Part Musical Structures -- Identification of Pure Painting Pigment Using Machine Learning Algorithms -- Evolving Neural Style Transfer Blends -- Evolving Image Enhancement Pipelines -- Genre Recognition from Symbolic Music with CNNs -- Axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks -- Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks -- Aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity -- Auralization of Three-Dimensional Cellular Automata -- Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction -- Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation -- The Enigma of Complexity -- SerumRNN: Step by Step Audio VST Effect Programming -- Parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks -- Raga Recognition in Indian Classical Music Using Deep Learning -- The Simulated Emergence of Chord Function -- Incremental Evolution of Stylized Images -- Dissecting Neural Networks Filter Responses for Artistic Style Transfer -- A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features -- A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation -- Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks -- "A Good Algorithm Does Not Steal - It Imitates": The Originality Report as a Means of Measuring when a Music Generation Algorithm Copies too Much -- From Music to Image - A Computational Creativity Approach -- “What is human?” A Turing Test for Artistic Creativity -- Mixed-Initiative Level Design with RL Brush -- Creating a Digital Mirror of Creative Practice -- An Application for Evolutionary Music Composition Using Autoencoders -- A Swarm Grammar-Based Approach to Virtual World Generation -- Co-Creative Drawing with One-Shot Generative Models. |
| Record Nr. | UNISA-996464386803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Intelligence in Music, Sound, Art and Design : 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández
| Artificial Intelligence in Music, Sound, Art and Design : 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (501 pages) : illustrations |
| Disciplina | 005.11 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Education—Data processing Machine learning Image processing—Digital techniques Computer vision Artificial intelligence Software engineering Theory of Computation Computers and Education Machine Learning Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Software Engineering |
| ISBN | 3-030-72914-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Sculpture Inspired Musical Composition, One Possible Approach -- Network Bending: Expressive Manipulation of Deep Generative Models -- SyVMO: Synchronous Variable Markov Oracle for Modeling and Predicting Multi-Part Musical Structures -- Identification of Pure Painting Pigment Using Machine Learning Algorithms -- Evolving Neural Style Transfer Blends -- Evolving Image Enhancement Pipelines -- Genre Recognition from Symbolic Music with CNNs -- Axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks -- Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks -- Aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity -- Auralization of Three-Dimensional Cellular Automata -- Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction -- Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation -- The Enigma of Complexity -- SerumRNN: Step by Step Audio VST Effect Programming -- Parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks -- Raga Recognition in Indian Classical Music Using Deep Learning -- The Simulated Emergence of Chord Function -- Incremental Evolution of Stylized Images -- Dissecting Neural Networks Filter Responses for Artistic Style Transfer -- A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features -- A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation -- Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks -- "A Good Algorithm Does Not Steal - It Imitates": The Originality Report as a Means of Measuring when a Music Generation Algorithm Copies too Much -- From Music to Image - A Computational Creativity Approach -- “What is human?” A Turing Test for Artistic Creativity -- Mixed-Initiative Level Design with RL Brush -- Creating a Digital Mirror of Creative Practice -- An Application for Evolutionary Music Composition Using Autoencoders -- A Swarm Grammar-Based Approach to Virtual World Generation -- Co-Creative Drawing with One-Shot Generative Models. |
| Record Nr. | UNINA-9910484699303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings / / edited by Juan Romero, Anikó Ekárt, Tiago Martins, João Correia
| Artificial Intelligence in Music, Sound, Art and Design [[electronic resource] ] : 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings / / edited by Juan Romero, Anikó Ekárt, Tiago Martins, João Correia |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (238 pages) : illustrations |
| Disciplina | 005.11 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Computer networks Compilers (Computer programs) Image processing—Digital techniques Computer vision Signal processing Theory of Computation Computer Communication Networks Compilers and Interpreters Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing |
| ISBN | 3-030-43859-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A deep learning neural network for classifying good and bad photos -- Adapting and Enhancing Evolutionary Art for Casual Creation -- Comparing Fuzzy Rule Based Approaches for Music Genre Classification -- Quantum Zentanglement: Combining Picbreeder and Wave Function Collapse to Create Zentangles -- Emerging Technology System Evolution -- Fusion of Hilbert-Huang Transform and Deep Convolutional Neural Network for Predominant Musical Instruments Recognition -- Genetic Reverb: Synthesizing Artificial Reverberant Fields Via Genetic Algorithms -- Portraits of No One: An Interactive Installation -- Understanding Aesthetic Evaluation with Deep Learning -- An Aesthetic-Based Fitness Measure and a Framework for Guidance of Evolutionary Design in Architecture -- Objective Evaluation of Tonal Fitness for Chord Progressions -- Coevolving Artistic Images Using OMNIREP -- Sound Cells in Genetic Improvisation: An Evolutionary Model for Improvised Music -- Controlling Self-Organization in Generative Creative Systems -- Emulation Games. See and Be Seen, a Subjective Approach to Analog Computational Neuroscience. |
| Record Nr. | UNISA-996418218203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Intelligence in Music, Sound, Art and Design : 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings / / edited by Juan Romero, Anikó Ekárt, Tiago Martins, João Correia
| Artificial Intelligence in Music, Sound, Art and Design : 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings / / edited by Juan Romero, Anikó Ekárt, Tiago Martins, João Correia |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (238 pages) : illustrations |
| Disciplina | 005.11 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer science
Computer networks Compilers (Computer programs) Image processing—Digital techniques Computer vision Signal processing Theory of Computation Computer Communication Networks Compilers and Interpreters Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing |
| ISBN | 3-030-43859-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A deep learning neural network for classifying good and bad photos -- Adapting and Enhancing Evolutionary Art for Casual Creation -- Comparing Fuzzy Rule Based Approaches for Music Genre Classification -- Quantum Zentanglement: Combining Picbreeder and Wave Function Collapse to Create Zentangles -- Emerging Technology System Evolution -- Fusion of Hilbert-Huang Transform and Deep Convolutional Neural Network for Predominant Musical Instruments Recognition -- Genetic Reverb: Synthesizing Artificial Reverberant Fields Via Genetic Algorithms -- Portraits of No One: An Interactive Installation -- Understanding Aesthetic Evaluation with Deep Learning -- An Aesthetic-Based Fitness Measure and a Framework for Guidance of Evolutionary Design in Architecture -- Objective Evaluation of Tonal Fitness for Chord Progressions -- Coevolving Artistic Images Using OMNIREP -- Sound Cells in Genetic Improvisation: An Evolutionary Model for Improvised Music -- Controlling Self-Organization in Generative Creative Systems -- Emulation Games. See and Be Seen, a Subjective Approach to Analog Computational Neuroscience. |
| Record Nr. | UNINA-9910409674303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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