Study on Perception-Action Scheme for Human-Robot Musical Interaction in Wind Instrumental Play

制度:新 ; 報告番号:甲3337号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/25 ; 早大学位記番号:新564

Robotics in Germany and Japan

This book comprehends an intercultural and interdisciplinary framework including current research fields like Roboethics, Hermeneutics of Technologies, Technology Assessment, Robotics in Japanese Popular Culture and Music Robots. Contributions on cultural interrelations, technical visions and essays are rounding out the content of this book

Towards Anthropomorphic Robot Thereminist

Theremin is an electronic musical instrument considered to be the most difficult to play which requires the players hands to have high precision and stability as any position change within proximity of the instruments antennae can make a difference to the pitch or volume. In a different direction to previous developments of Theremin playing robots, we propose a Humanoid Thereminist System that goes beyond using only one degree of freedom which will open up the possibility for robot to acquire more complex skills, such as aerial fingering and include musical expressions in playing the Theremin. The proposed system consists of two phases, namely calibration phase and playing phase which can be executed independently. During the playing phase, the System takes input from a MIDI file and performs path planning using a combination of minimum energy strategy in joint space and feedback error correction for next playing note. Three experiments have been conducted to evaluate the developed system quantitatively and qualitatively by playing a selection of music files. The experiments have demonstrated that the proposed system can effectively utilise multiple degrees of freedoms while maintaining minimum pitch error margins

Embodied Cognitive Science of Music. Modeling Experience and Behavior in Musical Contexts

Recently, the role of corporeal interaction has gained wide recognition within cognitive musicology. This thesis reviews evidence from different directions in music research supporting the importance of body-based processes for the understanding of music-related experience and behaviour. Stressing the synthetic focus of cognitive science, cognitive science of music is discussed as a modeling approach that takes these processes into account and may theoretically be embedded within the theory of dynamic systems. In particular, arguments are presented for the use of robotic devices as tools for the investigation of processes underlying human music-related capabilities (musical robotics)

Robotic arts: Current practices, potentials, and implications

Given that the origin of the “robot” comes from efforts to create a worker to help people, there has been relatively little research on making a robot for non-work purposes. However, some researchers have explored robotic arts since Leonardo da Vinci. Many questions can be posed regarding the potentials of robotic arts: (1) Is there anything we can call machine-creativity? (2) Can robots improvise artworks on the fly? and (3) Can art robots pass the Turing test? To ponder these questions and see the current status quo of robotic arts, the present paper surveys the contributions of robotics in diverse forms of arts, including drawing, theater, music, and dance. The present paper describes selective projects in each genre, core procedure, possibilities and limitations within the aesthetic computing framework. Then, the paper discusses implications of these robotic arts in terms of both robot research and art research, followed by conclusions including answers to the questions posed at the outset

AVISARME: Audio Visual Synchronization Algorithm for a Robotic Musician Ensemble

This thesis presents a beat detection algorithm which combines both audio and visual inputs to synchronize a robotic musician to its human counterpart. Although there has been considerable work done to create sophisticated methods for audio beat detection, the visual aspect of musicianship has been largely ignored. With advancements in image processing techniques, as well as both computer and imaging technologies, it has recently become feasible to integrate visual inputs into beat detection algorithms. Additionally, the proposed method for audio tempo detection also attempts to solve many issues that are present in current algorithms. Current audio-only algorithms have imperfections, whether they are inaccurate, too computationally expensive, or suffer from terrible resolution. Through further experimental testing on both a popular music database and simulated music signals, the proposed algorithm performed statistically better in both accuracy and robustness than the baseline approaches. Furthermore, the proposed approach is extremely efficient, taking only 45ms to compute on a 2.5s signal, and maintains an extremely high temporal resolution of 0.125 BPM. The visual integration also relies on Full Scene Tracking, allowing it to be utilized for live beat detection for practically all musicians and instruments. Numerous optimization techniques have been implemented, such as pyramidal optimization (PO) and clustering techniques which are presented in this thesis. A Temporal Difference Learning approach to sensor fusion and beat synchronization is also proposed and tested thoroughly. This TD learning algorithm implements a novel policy switching criterion which provides a stable, yet quickly reacting estimation of tempo. The proposed algorithm has been implemented and tested on a robotic drummer to verify the validity of the approach. The results from testing are documented in great detail and compared with previously proposed approaches

Musicianship for Robots with Style

ABSTRACT In this paper we introduce a System conceived to serve as the "musical brain" of autonomous musical robots or agent-based software simulations of robotic systems. Our research goal is to provide robots with the ability to integrate with the musical culture of their surroundings. In a multi-agent configuration, the System can simulate an environment in which autonomous agents interact with each other as well as with external agents (e.g., robots, human beings or other systems). The main outcome of these interactions is the transformation and development of their musical styles as well as the musical style of the environment in which they live

Timbral Learning for Musical Robots

abstract: The tradition of building musical robots and automata is thousands of years old. Despite this rich history, even today musical robots do not play with as much nuance and subtlety as human musicians. In particular, most instruments allow the player to manipulate timbre while playing; if a violinist is told to sustain an E, they will select which string to play it on, how much bow pressure and velocity to use, whether to use the entire bow or only the portion near the tip or the frog, how close to the bridge or fingerboard to contact the string, whether or not to use a mute, and so forth. Each one of these choices affects the resulting timbre, and navigating this timbre space is part of the art of playing the instrument. Nonetheless, this type of timbral nuance has been largely ignored in the design of musical robots. Therefore, this dissertation introduces a suite of techniques that deal with timbral nuance in musical robots. Chapter 1 provides the motivating ideas and introduces Kiki, a robot designed by the author to explore timbral nuance. Chapter 2 provides a long history of musical robots, establishing the under-researched nature of timbral nuance. Chapter 3 is a comprehensive treatment of dynamic timbre production in percussion robots and, using Kiki as a case-study, provides a variety of techniques for designing striking mechanisms that produce a range of timbres similar to those produced by human players. Chapter 4 introduces a machine-learning algorithm for recognizing timbres, so that a robot can transcribe timbres played by a human during live performance. Chapter 5 introduces a technique that allows a robot to learn how to produce isolated instances of particular timbres by listening to a human play an examples of those timbres. The 6th and final chapter introduces a method that allows a robot to learn the musical context of different timbres; this is done in realtime during interactive improvisation between a human and robot, wherein the robot builds a statistical model of which timbres the human plays in which contexts, and uses this to inform its own playing.Dissertation/ThesisDoctoral Dissertation Media Arts and Sciences 201