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Non-invasive gesture sensing, physical modeling, machine learning and acoustic actuation for pitched percussionTrail, Shawn 07 May 2018 (has links)
This thesis explores the design and development of digitally extended, electro- acoustic (EA) pitched percussion instruments, and their use in novel, multi-media performance contexts. The proposed techniques address the lack of expressivity in existing EA pitched percussion systems. The research is interdisciplinary in na- ture, combining Computer Science and Music to form a type of musical human- computer interaction (HCI) in which novel playing techniques are integrated in perfor- mances. Supporting areas include Electrical Engineering- design of custom hardware circuits/DSP; and Mechanical Engineering- design/fabrication of new instruments. The contributions can be grouped into three major themes: 1) non-invasive gesture recognition using sensors and machine learning, 2) acoustically-excited physical mod- els, 3) timbre-recognition software used to trigger idiomatic acoustic actuation. In addition to pitched percussion, which is the main focus of the thesis, application of these ideas to other music contexts is also discussed. / Graduate
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Digitizing North Indian music: preservation and extension using multimodal sensor systems, machine learning and roboticsKapur, Ajay 24 August 2007 (has links)
This dissertation describes how state of the art computer music technology can be used to digitize, analyze, preserve and extend North Indian classical music performance. Custom built controllers, influenced by the Human Computer Interaction (HCI) community, serve as new interfaces to gather musical gestures from a performing artist. Designs on how to modify a Tabla, Dholak, and Sitar with sensors and electronics are described. Experiments using wearable sensors to capture ancillary gestures of a human performer are also included. A twelve-armed solenoid-based robotic drummer was built to perform on a variety of traditional percussion instruments from around India. The dissertation also describes experimentation on interfacing a human sitar performer with the robotic drummer. Experiments include automatic tempo tracking and accompaniment methods. A framework is described for digitally transcribing performances of masters using custom designed hardware and software to aid in preservation. This work draws on knowledge from many disciplines including: music, computer science, electrical engineering, mechanical engineering and psychology. The goal is to set a paradigm on how to use technology to aid in the preservation of traditional art and culture.
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Digitizing North Indian music: preservation and extension using multimodal sensor systems, machine learning and roboticsKapur, Ajay 24 August 2007 (has links)
This dissertation describes how state of the art computer music technology can be used to digitize, analyze, preserve and extend North Indian classical music performance. Custom built controllers, influenced by the Human Computer Interaction (HCI) community, serve as new interfaces to gather musical gestures from a performing artist. Designs on how to modify a Tabla, Dholak, and Sitar with sensors and electronics are described. Experiments using wearable sensors to capture ancillary gestures of a human performer are also included. A twelve-armed solenoid-based robotic drummer was built to perform on a variety of traditional percussion instruments from around India. The dissertation also describes experimentation on interfacing a human sitar performer with the robotic drummer. Experiments include automatic tempo tracking and accompaniment methods. A framework is described for digitally transcribing performances of masters using custom designed hardware and software to aid in preservation. This work draws on knowledge from many disciplines including: music, computer science, electrical engineering, mechanical engineering and psychology. The goal is to set a paradigm on how to use technology to aid in the preservation of traditional art and culture.
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