Perceptual Learning of Natural and Sinewave Voices

Author: Sonya M. Sheffert, David B. Pisoni, Jennifer M. Fellowes, and Robert E. Romez

Abstract:
This report describes the results of a perceptual training study that was designed to explore how listeners learn to categorize novel voices and how knowledge of a familiar voice generalizes to novel utterances. The speech samples from which the listeners learned to identify individual were of two kinds: Naturally produced English sentences and sinewave replicas of these sentences. The sinewave items were nonspeech tonal patterns that preserved coarse-grained properties of the talker's vocal tract transfer function while eliminating traditional cues to voice quality. Listeners were trained over several days to identify by name ten talkers from sentence length sinewave or natural speech utterances. Knowledge about the talker's voice was then assessed using two generalization tests in which listeners heard a novel set of sentences and were required to identify the speaker. In one generalization test, the sentences were sinewave replicas whereas in the other generalization test, the sentences were naturally produced. The results showed that perceptual learning of a talker's voice can occur even when specific acoustic products of vocal articulation are eliminated from the signal. The data also showed that speaker-specific knowledge acquired during this perceptual training task generalized to novel natural and novel sinewave sentences. Variability in the degree of perceptual learning affected generalization of speaker knowledge. The results of this study show that listeners can learn about a talker's voice form highly impoverished acoustic signals when the products of vocal articulation are eliminated, and that this knowledge generalizes to novel utterances produced by these same talkers.