GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples

Archelaos  Vasileiou; João André Mafra  Tenera; Emmanouil  Papageorgiou; George Palamas

doi:10.1007/978-3-030-76426-5_8

GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples

Archelaos Vasileiou, João André Mafra Tenera, Emmanouil Papageorgiou, George Palamas

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

Abstract

This paper proposes a generative design approach for the creative exploration of dynamic soundscapes that can be used to generate compelling and immersive sound environments. A granular synthesis tool is considered based on the perceptual self-organization of sound samples by utilizing the t-Stochastic Neighboring Embedded algorithm (t-SNE) for the spatial mapping of sonic grains into a 2D space. The proposed system was able to relate the visual stimuli with the sonic responses in the context of the generic gestalt principles of visual perception. According to user evaluation, the application operated intuitively and also revealed the potential for creative expressiveness both from the user’s perspective and as a standalone, generative synthesizer.

Originalsprog	Engelsk
Titel	Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020
Redaktører	Navid Shaghaghi, Fabrizio Lamberti, Brian Beams, Reza Shariatmadar, Ahmed Amer
Vol/bind	377
Forlag	Springer
Publikationsdato	2021
Sider	118-130
ISBN (Trykt)	978-3-030-76425-8
ISBN (Elektronisk)	978-3-030-76426-5
DOI	https://doi.org/10.1007/978-3-030-76426-5_8
Status	Udgivet - 2021
Begivenhed	EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment - Online, Santa Clara, USA Varighed: 12 dec. 2020 → 14 dec. 2020 https://intetain.eai-conferences.org/2020/

Konference

Konference	EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment
Lokation	Online
Land/Område	USA
By	Santa Clara
Periode	12/12/2020 → 14/12/2020
Internetadresse	https://intetain.eai-conferences.org/2020/

Navn	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Vol/bind	377
ISSN	1867-8211

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10.1007/978-3-030-76426-5_8

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Citationsformater

Vasileiou, A., Tenera, J. A. M., Papageorgiou, E., & Palamas, G. (2021). GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. I N. Shaghaghi, F. Lamberti, B. Beams, R. Shariatmadar, & A. Amer (red.), Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020 (Bind 377, s. 118-130). Springer. https://doi.org/10.1007/978-3-030-76426-5_8

Vasileiou, Archelaos ; Tenera, João André Mafra ; Papageorgiou, Emmanouil et al. / GrainSynth : A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. red. / Navid Shaghaghi ; Fabrizio Lamberti ; Brian Beams ; Reza Shariatmadar ; Ahmed Amer. Bind 377 Springer, 2021. s. 118-130 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Bind 377).

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title = "GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples",

abstract = "This paper proposes a generative design approach for the creative exploration of dynamic soundscapes that can be used to generate compelling and immersive sound environments. A granular synthesis tool is considered based on the perceptual self-organization of sound samples by utilizing the t-Stochastic Neighboring Embedded algorithm (t-SNE) for the spatial mapping of sonic grains into a 2D space. The proposed system was able to relate the visual stimuli with the sonic responses in the context of the generic gestalt principles of visual perception. According to user evaluation, the application operated intuitively and also revealed the potential for creative expressiveness both from the user{\textquoteright}s perspective and as a standalone, generative synthesizer.",

author = "Archelaos Vasileiou and Tenera, {Jo{\~a}o Andr{\'e} Mafra} and Emmanouil Papageorgiou and George Palamas",

year = "2021",

doi = "10.1007/978-3-030-76426-5_8",

language = "English",

isbn = "978-3-030-76425-8",

volume = "377",

series = "Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering",

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editor = "Shaghaghi, {Navid } and Lamberti, {Fabrizio } and Beams, {Brian } and Shariatmadar, {Reza } and Amer, {Ahmed }",

booktitle = "Intelligent Technologies for Interactive Entertainment",

address = "Germany",

note = "EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment, intetain20 ; Conference date: 12-12-2020 Through 14-12-2020",

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Vasileiou, A, Tenera, JAM, Papageorgiou, E & Palamas, G 2021, GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. i N Shaghaghi, F Lamberti, B Beams, R Shariatmadar & A Amer (red), Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. bind 377, Springer, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, bind 377, s. 118-130, EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment, Santa Clara, USA, 12/12/2020. https://doi.org/10.1007/978-3-030-76426-5_8

GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. / Vasileiou, Archelaos; Tenera, João André Mafra ; Papageorgiou, Emmanouil et al.
Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. red. / Navid Shaghaghi; Fabrizio Lamberti; Brian Beams; Reza Shariatmadar; Ahmed Amer. Bind 377 Springer, 2021. s. 118-130 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Bind 377).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AB - This paper proposes a generative design approach for the creative exploration of dynamic soundscapes that can be used to generate compelling and immersive sound environments. A granular synthesis tool is considered based on the perceptual self-organization of sound samples by utilizing the t-Stochastic Neighboring Embedded algorithm (t-SNE) for the spatial mapping of sonic grains into a 2D space. The proposed system was able to relate the visual stimuli with the sonic responses in the context of the generic gestalt principles of visual perception. According to user evaluation, the application operated intuitively and also revealed the potential for creative expressiveness both from the user’s perspective and as a standalone, generative synthesizer.

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SN - 978-3-030-76425-8

VL - 377

T3 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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BT - Intelligent Technologies for Interactive Entertainment

A2 - Shaghaghi, Navid

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Vasileiou A, Tenera JAM, Papageorgiou E, Palamas G. GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. I Shaghaghi N, Lamberti F, Beams B, Shariatmadar R, Amer A, red., Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. Bind 377. Springer. 2021. s. 118-130. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Bind 377). doi: 10.1007/978-3-030-76426-5_8

GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples

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