  In this paper, we propose a method for removing linguistic information from
speech for the purpose of isolating paralinguistic indicators of affect. The
immediate utility of this method lies in clinical tests of sensitivity to vocal
affect that are not confounded by language, which is impaired in a variety of
clinical populations. The method is based on simultaneous recordings of speech
audio and electroglottographic (EGG) signals. The speech audio signal is used
to estimate the average vocal tract filter response and amplitude envelop. The
EGG signal supplies a direct correlate of voice source activity that is mostly
independent of phonetic articulation. The dynamic energy of the speech audio
and the average vocal tract filter are applied to the EGG signal create a third
signal designed to capture as much paralinguistic information from the vocal
production system as possible -- maximizing the retention of bioacoustic cues
to affect -- while eliminating phonetic cues to verbal meaning. To evaluate the
success of this method, we studied the perception of corresponding speech audio
and transformed EGG signals in an affect rating experiment with online
listeners. The results show a high degree of similarity in the perceived affect
of matched signals, indicating that our method is effective.
