Decoding soundscape stimuli and their impact on ASMR studies

This paper focuses on extracting and understanding the acoustical features embedded in the soundscape used in ASMR (Autonomous Sensory Meridian Response) studies. To this aim, a dataset of the most common sound effects employed in ASMR studies is gathered, containing whispering stimuli but also sound effects such as tapping and scratching. Further, a comparative analytical survey is performed based on various acoustical features and two-dimensional representations in the form of mel spectrogram. A special interest is in whispering sounds uttered in different languages. That is why whispering sounds are compared in the language context, and the characteristics of speaking and whispering are investigated within languages. The results of the 2D analyses are shown in the form of similarity measures, such as Normalized Root Mean Squared Error (NRMSE), PSNR (peak signal-to-noise ratio), and SSIM (structural similarity index measure). The summary is produced, showing that the analytical aspect of the inherently experiential nature of ASMR is highly affected by the subjective, personal experience, so the evidence behind triggering certain brain waves cannot be unambiguous.

Authors

Publication Details

Journal
International Journal of Electronics and Telecommunications
Published
2024-11-18
DOI
https://doi.org/10.24425/ijet.2024.152065
Citations
1
Primary Topic
Noise Effects and Management
Type
article
Field-Weighted Citation Impact
0.87
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article

Decoding soundscape stimuli and their impact on ASMR studies

Bożena Kostek, Sahar Seifzadeh, Tomasz Piernicki
1 citations
International Journal of Electronics and Telecommunications
Noise Effects and Management
0.87
article

Decoding soundscape stimuli and their impact on ASMR studies

Bożena Kostek, Sahar Seifzadeh, Tomasz Piernicki
article en
1 citations

Abstract

This paper focuses on extracting and understanding the acoustical features embedded in the soundscape used in ASMR (Autonomous Sensory Meridian Response) studies. To this aim, a dataset of the most common sound effects employed in ASMR studies is gathered, containing whispering stimuli but also sound effects such as tapping and scratching. Further, a comparative analytical survey is performed based on various acoustical features and two-dimensional representations in the form of mel spectrogram. A special interest is in whispering sounds uttered in different languages. That is why whispering sounds are compared in the language context, and the characteristics of speaking and whispering are investigated within languages. The results of the 2D analyses are shown in the form of similarity measures, such as Normalized Root Mean Squared Error (NRMSE), PSNR (peak signal-to-noise ratio), and SSIM (structural similarity index measure). The summary is produced, showing that the analytical aspect of the inherently experiential nature of ASMR is highly affected by the subjective, personal experience, so the evidence behind triggering certain brain waves cannot be unambiguous.

International Journal of Electronics and Telecommunications
Quality Education
Openalex Percentile: Top 19%
Noise Effects and Management
0.87
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