Glottal Features Under Workload in Human-Robot Interaction

We explore different ways of detecting the glottal feature changes when the subject is under workload. Glottal characteristics from speech production representing the vocal cord behavior will be discussed. We believe that workload of the human subject has specific impact on the behavior of the vocal folds, which may result in the variations in glottal flow. This paper investigates the variation of the glottal flow in workload state. Glottal source is discussed and the parameters from glottal flow representing the variations in workload are proposed. Through a study on a database containing over 700 voice signals from 11 speakers (four male and seven female), we prove that two glottal features (NAQ and CPR) are significantly modified due to the increased workload pressure, which will provide a standard in classification of two different states. Experimental results show that NAQ and CPR values of vowel segments are more effective than traditional features.