Electroglottography in Real-Time Feedback for Healthy Singing

Abstract: This master thesis describes early attempts at using electroglottography (EGG) to capture such changes in vocal fold vibration patterns that could be of interest to teachers of contemporary commercial music. After initial explorations, focus is placed on detecting potentially detrimental phonation; more specifically on the pressed quality often associated with loud singing in high register (belting). FonaDyn, a program written in the SuperCollider language, is used to detect pressedness using an algorithm based on K-means clustering of Fourier components of EGG cycles. Results indicate that pressedness affects phonation in ways detectable using EGG. Changes caused by pressedness seem to vary between registers and this variation is similar between subjects. Detection of pressedness in a subject is quite successful when training the algorithm on the same subject, but not always across subjects.