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

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › 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.

Original language	English
Title of host publication	Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020
Editors	Navid Shaghaghi, Fabrizio Lamberti, Brian Beams, Reza Shariatmadar, Ahmed Amer
Volume	377
Publisher	Springer
Publication date	2021
Pages	118-130
ISBN (Print)	978-3-030-76425-8
ISBN (Electronic)	978-3-030-76426-5
DOIs	https://doi.org/10.1007/978-3-030-76426-5_8
Publication status	Published - 2021
Event	EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment - Online, Santa Clara, United States Duration: 12 Dec 2020 → 14 Dec 2020 https://intetain.eai-conferences.org/2020/

Conference

Conference	EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment
Location	Online
Country/Territory	United States
City	Santa Clara
Period	12/12/2020 → 14/12/2020
Internet address	https://intetain.eai-conferences.org/2020/

Series	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Volume	377
ISSN	1867-8211

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Vasileiou, A., Tenera, J. A. M., Papageorgiou, E., & Palamas, G. (2021). GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. In N. Shaghaghi, F. Lamberti, B. Beams, R. Shariatmadar, & A. Amer (Eds.), Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020 (Vol. 377, pp. 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. editor / Navid Shaghaghi ; Fabrizio Lamberti ; Brian Beams ; Reza Shariatmadar ; Ahmed Amer. Vol. 377 Springer, 2021. pp. 118-130 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 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",

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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. in N Shaghaghi, F Lamberti, B Beams, R Shariatmadar & A Amer (eds), Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. vol. 377, Springer, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 377, pp. 118-130, EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment, Santa Clara, United States, 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. ed. / Navid Shaghaghi; Fabrizio Lamberti; Brian Beams; Reza Shariatmadar; Ahmed Amer. Vol. 377 Springer, 2021. p. 118-130 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 377).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - GrainSynth

T2 - EAI Intetain 2020 – 12th EAI International Conference on Intelligent Technologies for Interactive Entertainment

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AU - Tenera, João André Mafra

AU - Papageorgiou, Emmanouil

AU - Palamas, George

PY - 2021

Y1 - 2021

N2 - 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.

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.

UR - https://link.springer.com/book/10.1007/978-3-030-76426-5

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

M3 - Article in proceeding

SN - 978-3-030-76425-8

VL - 377

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

SP - 118

EP - 130

BT - Intelligent Technologies for Interactive Entertainment

A2 - Shaghaghi, Navid

A2 - Lamberti, Fabrizio

A2 - Beams, Brian

A2 - Shariatmadar, Reza

A2 - Amer, Ahmed

PB - Springer

Y2 - 12 December 2020 through 14 December 2020

ER -

Vasileiou A, Tenera JAM, Papageorgiou E, Palamas G. GrainSynth: A Generative Synthesis Tool based on Spatial Interpretations of Sound Samples. In Shaghaghi N, Lamberti F, Beams B, Shariatmadar R, Amer A, editors, Intelligent Technologies for Interactive Entertainment : 12th EAI International Conference, INTETAIN 2020. Vol. 377. Springer. 2021. p. 118-130. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 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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