A psychoacoustic method to find the perceptual cues of stop consonants in natural speech.

Abstract

Synthetic speech has been widely used in the study of speech cues. A serious disadvantage of this method is that it requires prior knowledge about the cues to be identified in order to synthesize the speech. Incomplete or inaccurate hypotheses about the cues often lead to speech sounds of low quality. In this research a psychoacoustic method, named three-dimensional deep search (3DDS), is developed to explore the perceptual cues of stop consonants from naturally produced speech. For a given sound, it measures the contribution of each subcomponent to perception by time truncating, highpass/lowpass filtering, or masking the speech with white noise. The AI-gram, a visualization tool that simulates the auditory peripheral processing, is used to predict the audible components of the speech sound. The results are generally in agreement with the classical studies that stops are characterized by a short duration burst followed by a F2 transition, suggesting the effectiveness of the 3DDS method. However, it is also shown that /ba/ and /pa/ may have a wide band click as the dominant cue. F2 transition is not necessary for the perception of /ta/ and /ka/. Moreover, many stop consonants contain conflicting cues that are characteristic of competing sounds. The robustness of a consonant sound to noise is determined by the intensity of the dominant cue.