Robotic musicianship : embodied artificial creativity and mechatronic musical expression

Robotic musicianship : embodied artificial creativity and mechatronic musical expression / Gil Weinberg, Mason Bretan, Guy Hoffman, Scott Driscoll.

This book discusses the principles, methodologies, and challenges of robotic musicianship through an in-depth review of the work conducted at the Georgia Tech Center for Music Technology (GTCMT), where the concept was first developed. Robotic musicianship is a relatively new research field that focu...

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Bibliographic Details
Main Authors: Weinberg, Gil (Author), Bretan, Mason (Author), Hoffman, Guy (Author), Driscoll, Scott (Author)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, [2020]
Series:Automation, collaboration, & e-services.
Subjects:
Artificial intelligence > Musical applications.
Computer music.
Robots.
Artificial intelligence > Musical applications
Computer music
Robots
Online Access:Click for online access
Table of Contents:
  • Intro
  • Foreword
  • Preface
  • Contents
  • 1 Introduction
  • 1.1 Abstract
  • 1.2 Why Robotic Musicianship
  • 1.3 Sound Production and Design-Survey
  • 1.3.1 Traditional Instruments
  • 1.3.2 Augmented and Novel Instruments
  • 1.4 Musical Intelligence
  • 1.4.1 Sensing and Perception
  • 1.4.2 Music Generation
  • 1.5 Embodiment
  • 1.6 Integrating Robotic Musicianship into New Interfaces
  • 1.6.1 Musical Companion Robots
  • 1.6.2 Wearable Robotic Musicians
  • 1.7 Discussion
  • References
  • 2 Platforms-Georgia Tech's Robotic Musicians
  • 2.1 Abstract
  • 2.2 Haile-A Robotic Percussionist
  • 2.2.1 Motivation
  • 2.2.2 Design
  • 2.3 Shimon-A Robotic Marimba Player
  • 2.3.1 Striker Design
  • 2.3.2 Mallet Motor Control
  • 2.3.3 Slider Motor Control
  • 2.3.4 Shimon's Socially Expressive Head
  • 2.4 Shimi-A Music Driven Robotic Dancing Companion
  • 2.4.1 Robotic Musical Companionship
  • 2.4.2 Design
  • 2.4.3 Software Architecture
  • 2.4.4 Core Capabilities
  • 2.5 The Robotic Drumming Prosthetic
  • 2.5.1 Motivation
  • 2.5.2 Related Work
  • 2.5.3 Platform
  • 2.5.4 Generative Physical Model for Stroke Generation
  • 2.5.5 Conclusions
  • References
  • 3 ``Listen Like A Human''-Human-Informed Music Perception Models
  • 3.1 Abstract
  • 3.2 Rhythmic Analysis of Live Drumming
  • 3.2.1 Onset Detection
  • 3.2.2 Beat Detection
  • 3.2.3 Rhythmic Stability and Similarity
  • 3.2.4 User Study
  • 3.3 Tonal Music Analysis Using Symbolic Rules
  • 3.3.1 Implementation
  • 3.3.2 Evaluation
  • 3.4 Music Analysis Using Deep Neural Networks
  • 3.4.1 Deep Musical Autoencoder
  • 3.4.2 Music Reconstruction Through Selection
  • 3.5 Real-Time Audio Analysis of Prerecorded Music
  • 3.5.1 Introduction
  • 3.5.2 Previous Work
  • 3.5.3 System Design
  • 3.5.4 Live Audio Analysis
  • 3.5.5 Gesture Design
  • 3.5.6 Network Design
  • 3.5.7 User Study
  • 3.5.8 Summary
  • References
  • 4 ``Play Like A Machine''-Generative Musical Models for Robots
  • 4.1 Abstract
  • 4.2 Genetic Algorithms
  • 4.2.1 Related Work
  • 4.2.2 Method
  • 4.3 Markov Processes (``Playing with the Masters'')
  • 4.3.1 Related Work
  • 4.3.2 Implementation
  • 4.3.3 Summary
  • 4.4 Path Planning Driven Music Generation
  • 4.4.1 Search and Path Planning
  • 4.4.2 Musical Path Planning
  • 4.4.3 Planning
  • 4.4.4 Evaluation
  • 4.4.5 Discussion
  • 4.5 Rule Based Jazz Improvisation
  • 4.5.1 Parametrized Representations of Higher-Level Musical Semantics
  • 4.5.2 Joint Optimization
  • 4.5.3 Musical Results
  • 4.5.4 Discussion
  • 4.6 Neural Network Based Improvisation
  • 4.6.1 Introduction
  • 4.6.2 Semantic Relevance
  • 4.6.3 Concatenation Cost
  • 4.6.4 Ranking Units
  • 4.6.5 Evaluating the Model
  • 4.6.6 Discussion
  • 4.6.7 Subjective Evaluation
  • 4.6.8 Results
  • 4.6.9 An Embodied Unit Selection Process
  • 4.7 Conclusion
  • References
  • 5 ``Be Social''-Embodied Human-Robot Musical Interactions
  • 5.1 Abstract
  • 5.2 Embodied Interaction with Haile
  • 5.2.1 Interaction Modes

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