Modeling The Effect of Background Sounds on Human Focus Using Brain Decoding Technology

Abstract

The goal of this study was to learn what properties of sound affect human focus the most. Participants (N=62, 18-65y) performed various tasks while listening to either no background sound (silence), popular music playlists for increasing focus (pre-recorded songs), or personalized soundscapes (audio composed in real-time to increase a specific individual's focus). While performing tasks on a tablet, participants wore headphones and brain signals were recorded using a portable electroencephalography headband. Participants completed four one-hour long sessions, each with different audio content, at home. We successfully generated brain-based models to predict individual participant focus levels over time and used these models to analyze the effects of various audio content during different tasks. We found that while participants were working, personalized soundscapes increased their focus significantly above silence (p=0.008), while music playlists did not have a significant effect. For the young adult demographic (18-36y), silence was significantly less effective at producing focus than audio content of any type tested (p=0.001-0.009). Personalized soundscapes enhanced focus the most relative to silence, but professionally crafted playlists of pre-recorded songs also increased focus during specific time intervals, especially for the youngest audience demographic. We also found that focus levels can be predicted from physical properties of sound, enabling human and artificial intelligence composers to test and refine audio to produce increases or decreases in listener focus with high temporal (millisecond) precision. Future research includes real-time adjustment of sound for other functional objectives, such as affecting listener enjoyment, calm, or memory.