Artificial ASMR : A Cyber-Psychological Approach

Zexin FANG; Bin HAN; Clark C. CAO; Hans D. SCHOTTEN

doi:10.1109/MLSP55844.2023.10285977

Artificial ASMR : A Cyber-Psychological Approach

Zexin FANG, Bin HAN, Clark C. CAO, Hans D. SCHOTTEN

Lingnan University

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

The popularity of Autonomous Sensory Meridian Response (ASMR) has sky-rockted over the past decade, but scientific studies on what exactly triggered ASMR effect remain few and immature, one most commonly acknowledged trigger is that ASMR clips typically provide rich semantic information. With our attention caught by the common acoustic patterns in ASMR audios, we investigate the correlation between the cyclic features of audio signals and their effectiveness in triggering ASMR effects. A cyber-psychological approach that combines signal processing, artificial intelligence, and experimental psychology is taken, with which we are able to quantize ASMR-related acoustic features, and therewith synthesize ASMR clips with random cyclic patterns but not delivering identifiably scenarios to the audience, which were proven to be effective in triggering ASMR effects.

Original language	English
Title of host publication	2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)
Editors	Danilo COMMINIELLO, Michele SCARPINITI
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9798350324112
ISBN (Print)	9798350324112
DOIs	https://doi.org/10.1109/MLSP55844.2023.10285977
Publication status	Published - 23 Oct 2023
Event	2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) - Rome, Italy, Rome, Italy Duration: 17 Sept 2023 → 20 Sept 2023

Conference

Conference	2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)
Country/Territory	Italy
City	Rome
Period	17/09/23 → 20/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

ASMR
auditory
cyclostationary
GAN

Access to Document

10.1109/MLSP55844.2023.10285977

https://ieeexplore.ieee.org/document/10285977/

Cite this

@inproceedings{fd81839576ac490788e287075e00129d,

title = "Artificial ASMR : A Cyber-Psychological Approach",

abstract = "The popularity of Autonomous Sensory Meridian Response (ASMR) has sky-rockted over the past decade, but scientific studies on what exactly triggered ASMR effect remain few and immature, one most commonly acknowledged trigger is that ASMR clips typically provide rich semantic information. With our attention caught by the common acoustic patterns in ASMR audios, we investigate the correlation between the cyclic features of audio signals and their effectiveness in triggering ASMR effects. A cyber-psychological approach that combines signal processing, artificial intelligence, and experimental psychology is taken, with which we are able to quantize ASMR-related acoustic features, and therewith synthesize ASMR clips with random cyclic patterns but not delivering identifiably scenarios to the audience, which were proven to be effective in triggering ASMR effects.",

keywords = "ASMR, auditory, cyclostationary, GAN",

author = "Zexin FANG and Bin HAN and CAO, {Clark C.} and SCHOTTEN, {Hans D.}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) ; Conference date: 17-09-2023 Through 20-09-2023",

year = "2023",

month = oct,

day = "23",

doi = "10.1109/MLSP55844.2023.10285977",

language = "English",

isbn = "9798350324112",

editor = "Danilo COMMINIELLO and Michele SCARPINITI",

booktitle = "2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)",

publisher = "IEEE",

}

FANG, Z, HAN, B, CAO, CC & SCHOTTEN, HD 2023, Artificial ASMR : A Cyber-Psychological Approach. in D COMMINIELLO & M SCARPINITI (eds), 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)., Code 193936, IEEE, 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP), Rome, Italy, 17/09/23. https://doi.org/10.1109/MLSP55844.2023.10285977

Artificial ASMR : A Cyber-Psychological Approach. / FANG, Zexin; HAN, Bin; CAO, Clark C. et al.
2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP). ed. / Danilo COMMINIELLO; Michele SCARPINITI. IEEE, 2023. Code 193936.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Artificial ASMR : A Cyber-Psychological Approach

AU - FANG, Zexin

AU - HAN, Bin

AU - CAO, Clark C.

AU - SCHOTTEN, Hans D.

PY - 2023/10/23

Y1 - 2023/10/23

N2 - The popularity of Autonomous Sensory Meridian Response (ASMR) has sky-rockted over the past decade, but scientific studies on what exactly triggered ASMR effect remain few and immature, one most commonly acknowledged trigger is that ASMR clips typically provide rich semantic information. With our attention caught by the common acoustic patterns in ASMR audios, we investigate the correlation between the cyclic features of audio signals and their effectiveness in triggering ASMR effects. A cyber-psychological approach that combines signal processing, artificial intelligence, and experimental psychology is taken, with which we are able to quantize ASMR-related acoustic features, and therewith synthesize ASMR clips with random cyclic patterns but not delivering identifiably scenarios to the audience, which were proven to be effective in triggering ASMR effects.

AB - The popularity of Autonomous Sensory Meridian Response (ASMR) has sky-rockted over the past decade, but scientific studies on what exactly triggered ASMR effect remain few and immature, one most commonly acknowledged trigger is that ASMR clips typically provide rich semantic information. With our attention caught by the common acoustic patterns in ASMR audios, we investigate the correlation between the cyclic features of audio signals and their effectiveness in triggering ASMR effects. A cyber-psychological approach that combines signal processing, artificial intelligence, and experimental psychology is taken, with which we are able to quantize ASMR-related acoustic features, and therewith synthesize ASMR clips with random cyclic patterns but not delivering identifiably scenarios to the audience, which were proven to be effective in triggering ASMR effects.

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KW - cyclostationary

KW - GAN

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M3 - Conference paper (refereed)

SN - 9798350324112

BT - 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)

A2 - COMMINIELLO, Danilo

A2 - SCARPINITI, Michele

PB - IEEE

T2 - 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)

Y2 - 17 September 2023 through 20 September 2023

ER -

Artificial ASMR : A Cyber-Psychological Approach

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Why Do We Pay to See Mummies and Zombie Movies: The Consumption of Dead Bodies

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Artificial ASMR : A Cyber-Psychological Approach

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Bibliographical note

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Why Do We Pay to See Mummies and Zombie Movies: The Consumption of Dead Bodies

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