Abstract

Phonemic restoration is a powerful auditory illusion in which listeners "hear" parts of words that are not really there. In earlier studies of the illusion, segments of words (phonemes) were replaced by an extraneous sound; listeners were asked whether anything was missing and where the extraneous noise had occurred. Most listeners reported that the utterance was intact and mislocalized the noise, suggesting that they had restored the missing phoneme. In the present study, a second type of stimulus was also presented: items in which the extraneous sound was merely superimposed on the critical phoneme. On each trial, listeners were asked to report whether they thought a stimulus utterance was intact (noise superimposed) or not (noise replacing). Since this procedure yields both a miss rate P(intact/replaced), and a false alarm rate P(replaced/intact), signal detection parameters of discriminability and bias can be calculated. The discriminability parameter reflects how similar the two types of stimuli sound; perceptual restoration of replaced items should make them sound intact, producing low discriminability scores. The bias parameter measures the tendency of listeners to report utterances as intact; it reflects postperceptual decision processes. This improved methodology was used to test the hypothesis that restoration (and more generally, speech perception) depends upon the bottom-up confirmation of expectations generated at higher levels. Perceptual restoration varied greatly wih the phone class of the replaced segment and its acoustic similarity to the replacement sound, supporting a bottom-up component to the illusion. Increasing listeners' expectations of a phoneme increased perceptual restoration: missing segments in words were better restored than corresponding pieces in phonologically legal pseudowords; priming the words produced even more restoration. In contrast, sentential context affected the postperceptual decision stage, biasing listeners to report utterances as intact. A limited interactive model of speech perception, with both bottom-up and top-down components, is used to explain the results.

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