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Kivanç Tatar

Biographic Data

ID1450171
NAMEKivanç Tatar
GIVEN NAMESKivanç
FAMILY NAMETatar
SIGNATURETATAR K
AFFILIATIONSChalmers University of Technology
ORCID0000-0003-4133-8641
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS3
WORKS AS AUTHOR6
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2016
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Revising research practices for singing data collection

    Open Access•Kelsey Cotton, Andre Holzapfel et al.•ARTICLE•AI & Society•2026

    As AI voice synthesis enables increasingly sophisticated vocal deepfakes and non-consensual voice cloning, the governance, licensing and access of singing datasets has become an urgent concern for data-contributors, who face significant harms from downstream and non-consensual usage of their singing data. Singing datasets are foundational to the development of high fidelity voice AI synthesis, yet current data collection practices pose challenges…

  • Imploding between the facts and concerns

    Open Access•Kelsey Cotton, Anna-Kaisa Kaila et al.•ARTICLE•Humanities and Social Sciences…•2025

    The advancement of AI-tools for musical performance has inspired exciting opportunities for interaction with musical-AI-agents. Interactions between humans and AI-agents in musical settings entail dynamic exchanges of control and power, and framings of AI-agents’ roles by human performers. We probe these framings and power-control exchanges through qualitative thematic lenses, drawing from post-phenomenology, matters of fact and concern and femin…

  • A Shift in Artistic Practices through Artificial Intelligence

    Kivanç Tatar, Petter Ericson et al.•ARTICLE•Leonardo•2024•References: 7

    The explosion of content generated by artificial intelligence (AI) models has initiated a cultural shift in arts, music, and media, whereby roles are changing, values are shifting, and conventions are challenged. The vast, readily available dataset of the Internet has created an environment for AI models to be trained on any content on the Web. With AI models shared openly and used by many globally, how does this new paradigm shift challenge the …

  • Respire

    Kivanç Tatar, Mirjana Prpa et al.•ARTICLE•Leonardo Music Journal•2019

    Respire is an immersive art piece that brings together three components: an immersive virtual reality (VR) environment, embodied interaction (via a breathing sensor) and a musical agent system to generate unique experiences of augmented breathing. The breathing sensor controls the user’s vertical elevation of the point of view under and over the virtual ocean. The frequency and patterns of breathing data guide the arousal of the musical agent, an…

  • Musical agents

    Kivanç Tatar, Philippe Pasquier•ARTICLE•Journal of New Music Research•2019•Cited by: 2•References: 68

    Musical agents are artificial agents that tackle musical creative tasks, partially or completely. This review of musical agents combines the terminology of Generative Arts (artistic practice) and the scientific literature of Computational Creativity, Multi-Agent Systems (MAS), and Artificial Intelligence. We define Musical Metacreation as a field that studies the partial or complete automation of musical tasks. We survey seventy-eight musical age…

  • Automatic Synthesizer Preset Generation with PresetGen

    Kivanç Tatar, Kıvanç Tatar et al.•ARTICLE•Journal of New Music Research•2016•Cited by: 1•References: 15

    We refer the task of finding preset(s) (i.e. set(s) of synthesizer parameters) that approximates a target sound best, as the preset generation problem. PresetGen addresses this problem regarding the real world synthesizer, OP-1. The OP-1 consists of several synthesis blocks, and it is not fully deterministic. We propose and evaluate a solution to preset generation using a multi-objective Non-dominated Sorting-Genetic-Algorithm-II. PresetGen handl…

  • Musical agents

    Kivanç Tatar, Philippe Pasquier•ARTICLE•Journal of New Music Research•2019•Cited by: 2•References: 68

    Musical agents are artificial agents that tackle musical creative tasks, partially or completely. This review of musical agents combines the terminology of Generative Arts (artistic practice) and the scientific literature of Computational Creativity, Multi-Agent Systems (MAS), and Artificial Intelligence. We define Musical Metacreation as a field that studies the partial or complete automation of musical tasks. We survey seventy-eight musical age…

  • Automatic Synthesizer Preset Generation with PresetGen

    Kivanç Tatar, Kıvanç Tatar et al.•ARTICLE•Journal of New Music Research•2016•Cited by: 1•References: 15

    We refer the task of finding preset(s) (i.e. set(s) of synthesizer parameters) that approximates a target sound best, as the preset generation problem. PresetGen addresses this problem regarding the real world synthesizer, OP-1. The OP-1 consists of several synthesis blocks, and it is not fully deterministic. We propose and evaluate a solution to preset generation using a multi-objective Non-dominated Sorting-Genetic-Algorithm-II. PresetGen handl…

  • Automatic Synthesizer Preset Generation with PresetGen

    Kivanç Tatar, Kıvanç Tatar et al.•ARTICLE•Journal of New Music Research•2016•Cited by: 1•References: 15

    We refer the task of finding preset(s) (i.e. set(s) of synthesizer parameters) that approximates a target sound best, as the preset generation problem. PresetGen addresses this problem regarding the real world synthesizer, OP-1. The OP-1 consists of several synthesis blocks, and it is not fully deterministic. We propose and evaluate a solution to preset generation using a multi-objective Non-dominated Sorting-Genetic-Algorithm-II. PresetGen handl…

  • Respire

    Kivanç Tatar, Mirjana Prpa et al.•ARTICLE•Leonardo Music Journal•2019

    Respire is an immersive art piece that brings together three components: an immersive virtual reality (VR) environment, embodied interaction (via a breathing sensor) and a musical agent system to generate unique experiences of augmented breathing. The breathing sensor controls the user’s vertical elevation of the point of view under and over the virtual ocean. The frequency and patterns of breathing data guide the arousal of the musical agent, an…

  • Musical agents

    Kivanç Tatar, Philippe Pasquier•ARTICLE•Journal of New Music Research•2019•Cited by: 2•References: 68

    Musical agents are artificial agents that tackle musical creative tasks, partially or completely. This review of musical agents combines the terminology of Generative Arts (artistic practice) and the scientific literature of Computational Creativity, Multi-Agent Systems (MAS), and Artificial Intelligence. We define Musical Metacreation as a field that studies the partial or complete automation of musical tasks. We survey seventy-eight musical age…

  • A Shift in Artistic Practices through Artificial Intelligence

    Kivanç Tatar, Petter Ericson et al.•ARTICLE•Leonardo•2024•References: 7

    The explosion of content generated by artificial intelligence (AI) models has initiated a cultural shift in arts, music, and media, whereby roles are changing, values are shifting, and conventions are challenged. The vast, readily available dataset of the Internet has created an environment for AI models to be trained on any content on the Web. With AI models shared openly and used by many globally, how does this new paradigm shift challenge the …

  • Imploding between the facts and concerns

    Open Access•Kelsey Cotton, Anna-Kaisa Kaila et al.•ARTICLE•Humanities and Social Sciences…•2025

    The advancement of AI-tools for musical performance has inspired exciting opportunities for interaction with musical-AI-agents. Interactions between humans and AI-agents in musical settings entail dynamic exchanges of control and power, and framings of AI-agents’ roles by human performers. We probe these framings and power-control exchanges through qualitative thematic lenses, drawing from post-phenomenology, matters of fact and concern and femin…

  • Revising research practices for singing data collection

    Open Access•Kelsey Cotton, Andre Holzapfel et al.•ARTICLE•AI & Society•2026

    As AI voice synthesis enables increasingly sophisticated vocal deepfakes and non-consensual voice cloning, the governance, licensing and access of singing datasets has become an urgent concern for data-contributors, who face significant harms from downstream and non-consensual usage of their singing data. Singing datasets are foundational to the development of high fidelity voice AI synthesis, yet current data collection practices pose challenges…

Music Technology and Sound Studies (5 works) · Art (4 works) · Computer Science (4 works) · Visual arts (4 works) · Musical (3 works) · Artificial Intelligence (2 works) · Human–computer interaction (2 works) · Mathematics (2 works) · Music and Audio Processing (2 works) · Psychology (2 works)

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