The Bioacoustics Lab

This project, in collaboration with Dr. Jan Svec at the Palacky  University Olomouc, Czech Republic, is developing new visualization tools to understand vocal fold dynamics in humans and other mammals. These are based on electroglottography and are verified using high-speed video in an excised larynx setup. Other collaborators on this project include Prof. Gerald Weissengruber at the University of Veterinary Medicine, Vienna.

Humidified heated air is blown through an excised larynx mounted on a laboratory bench. Vocal fold vibration and correlated data are documented by simultaneous recording of high-speed imaging data (6000 fps), acoustic signal, sound pressure level, electroglottographic signal, airflow, air pressure etc. Various methods and tools are currently being developed to aid in processing and analyzing the captured data (see sections below). The collected evidence is used to (a) gain a better understanding of vocal fold vibratory features, such as registers and chaos; and to (b) study the voice source properties of animal species not yet researched.

We have developed a new method for analyzing and displaying electroglottographic (EGG) signals (and their first derivative, DEGG): the electroglottographic wavegram. The wavegram provides an intuitive means for quickly assessing vocal fold contact phenomena and their variation over time. Vocal fold closing and opening appears here as a sequence of events rather than single incidents, taking place over a certain period of time, and changing with pitch, loudness and register. Multiple DEGG peaks which can occur during both the concacting and de-contacting phase of vocal fold vibration, are revealed in wavegrams to behave systematically, indicating subtle changes of vocal fold oscillatory regime. As such, EGG wavegrams promise to reveal more physiological information on vocal fold closure and opening events than previous methods.

To construct a wavegram, the time-varying fundamental frequency is calculated and consecutive individual glottal cycles are identified. Each cycle is locally normalized in duration and amplitude, the signal values are encoded by color intensity and the cycles are concatenated to display the entire phonation in a single image, similar as done in sound spectrography.