Enhancing Vocal Performance Through Computer-Assisted Training

Abstract

In the evolving landscape of vocal pedagogy, the integration of computer-assisted technologies represents a transformative shift from traditional master-apprentice models. This study investigates the efficacy of computer-assisted vocal training methods compared to conventional approaches, focusing on improvements in pitch accuracy, vocal range expansion, and emotional expression among novice vocalists. Utilizing a mixed-methods approach, including digital signal processing, machine learning, and virtual reality, the authors conducted a 12-week experiment involving 60 participants randomly divided into two groups. Results indicate that computer-assisted training offers nearly double the improvement in pitch accuracy and vocal range expansion over traditional methods, with more pronounced enhancements in emotional expression skills. These findings contribute significantly to developing standardized, personalized, and scientifically-grounded vocal training methodologies, demonstrating a more efficient pathway for enhancing vocal performance.