Software implementations and analyses of the emotional impact of various binaural beat classifications layered into music.

This study explores the psychoacoustic effects of binaural beats, which are produced when sinusoidal waves of slightly differing frequencies are played into each ear, leading to brainwave entrainment. Binaural beats are categorized by frequency bands (e.g., Beta: 14–30 Hz for energy, Theta: 4–8 Hz for relaxation), each associated with different psychological effects. This research contributes to the field by empirically analyzing whether binaural beats alter the emotional impact of music. Past studies have investigated the potential benefits of binaural beats in relaxation and energy stimulation. However, their effects, when combined with music, especially regarding a song's perceived emotional quality or valence, remain underexplored. The methodology involved developing a Binaural Synthesizer VST plugin using the JUCE C++ software framework for binaural beat synthesis with proper audio signal processing and buffering infrastructure; this encourages the use of binaural beats in music production workflows. Songs were categorized based on valence using Spotify’s API and mixed with either Beta or Theta binaural beats. Participants listened to both control and modified versions of these songs and provided valence ratings, noting changes on a scale ranging from significant decrease to significant increase. The randomized order of presentation and matched musical elements helped isolate binaural beat effects and minimize bias and fatigue. Results indicated that Beta beats consistently decreased valence in high-valence songs, contrary to expectations, while Theta beats also decreased valence in low-valence songs, aligning with the hypothesis. These findings suggest that binaural beats decrease perceived positiveness in music rather than enhancing energy or relaxation. Limitations include the short duration of exposure and the subjective nature of emotional assessment, warranting further research.