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230704 ||| eng |
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|a 9783031353826
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|a Aramaki, Mitsuko
|e [editor]
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| 245 |
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|a Music in the AI Era
|h Elektronische Ressource
|b 15th International Symposium, CMMR 2021, Virtual Event, November 15–19, 2021, Revised Selected Papers
|c edited by Mitsuko Aramaki, Keiji Hirata, Tetsuro Kitahara, Richard Kronland-Martinet, Sølvi Ystad
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| 250 |
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|a 1st ed. 2023
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2023, 2023
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| 300 |
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|a XI, 332 p. 135 illus., 96 illus. in color
|b online resource
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|a With Love: Electroacoustic, Audiovisual, and Telematic Music
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|a Music technology in the IA era -- KANSEI Informatics and Music Technology in AI Era -- On Parallelism in Music and Language: A Perspective from Symbol Emergence Systems based on Probabilistic Generative Models -- WaVAEtable Synthesis -- Deep Learning-based Music Instrument Recognition: Exploring Learned Feature Representations -- Time-span Tree Leveled by Duration of Time-span -- Evaluating AI as an Assisting Tool to Create Electronic Dance Music -- Interactive systems for music -- Suiview: A Web-based Application that Enables Users to Practice Wind Instrument Performance -- Continuous Parameter Control Using an On/Off Sensor in the Augmented Handheld Triangle -- Networked and Collaborative Musical Play Amongst Humans and Virtual Biological Agents in Locus Diffuse -- Towards an Aesthetic of Hybrid Performance Practice -- Development of Audio Descriptors Inspired by Schaefferian Criteria: a Set of Tools for Interactive Exploration of Percussive Sounds --
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|a A Polytemporal Model for Musical Scheduling -- Interaction Strategies in Composition for Karlax and Acoustic Instruments -- Music Information Retrieval and Modeling -- Modelling Moral Traits with Music Listening Preferences and Demographics -- Classification of 1950 to 1960 Electronic Music Using the VGGish Neural Network and Random Forest -- Knowledge Transfer from Neural Networks for Speech Music Classification -- Predominant Instrument Recognition in Polyphonic Music Using Convolutional Recurrent Neural Networks -- The Matrix Profile for Motif Discovery in Audio - An Example Application in Carnatic Music -- A Rule-based Method for Implementing Implication-Realization Model -- Music and Performance Analysis -- CROCUS: Dataset of Critique Documents of Musical Performance -- A Psychoacoustic-Based Methodology for Sound Mass Music Analysis -- Musical Structure Analysis and Generation through Abstraction Trees -- Analysis of Musical Dynamics in Vocal Performances --
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|a Computer Communication Networks
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|a User interfaces (Computer systems)
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|a Image processing / Digital techniques
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|a Education / Data processing
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|a Computer vision
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|a Artificial Intelligence
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|a Computers and Education
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|a Computer networks
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|a Computer Imaging, Vision, Pattern Recognition and Graphics
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|a Artificial intelligence
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|a User Interfaces and Human Computer Interaction
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| 653 |
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|a Human-computer interaction
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| 700 |
1 |
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|a Hirata, Keiji
|e [editor]
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| 700 |
1 |
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|a Kitahara, Tetsuro
|e [editor]
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| 700 |
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|a Kronland-Martinet, Richard
|e [editor]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Lecture Notes in Computer Science
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| 028 |
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|a 10.1007/978-3-031-35382-6
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| 856 |
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|u https://doi.org/10.1007/978-3-031-35382-6?nosfx=y
|x Verlag
|3 Volltext
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|a 004.019
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|a 005.437
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|a This book constitutes the refereed proceedings and revised selected papers from the 15th International Symposium on Music in the AI Era, CMMR 2021, which took place during November 15–19, 2021 as a virtual event. The 24 full papers included in this book were carefully reviewed and selected from 48 submissions. The papers are grouped in thematical sessions on Music technology in the IA era; Interactive systems for music; Music Information Retrieval and Modeling; and Music and Performance Analysis
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