The popularity of Autonomous Sensory Meridian Response (ASMR) has skyrockteted over the past decade, but scientific studies on it are still few and immature. With our attention caught by the common acoustic patterns in ASMR audios, we investigate the correlation between the time-frequency and 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 identify ASMR-related acoustic features, and therewith synthesize random artificial ASMR audios.
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