Publications

Abstract

Accommodating talker variability is a complex and multi-layered cognitive process. It involves shifting attention to the vocal characteristics of the talker as well as the linguistic content of their speech. Due to an interdependence between voice and phonological processing, multi-talker
environments typically incur additional processing costs compared to single-talker environments. A failure or inability to efficiently distribute attention over multiple acoustic cues in the speech signal
may have detrimental language learning consequences. Yet, no studies have examined effects of multi-talker processing in populations with atypical perceptual, social and language processing for communication, including autistic people. Employing a classic word-monitoring task, we investigated
effects of talker variability in Australian English autistic (n = 24) and non-autistic (n = 28) adults.
Listeners responded to target words (e.g., apple, duck, corn) in randomised sequences of words. Half of the sequences were spoken by a single talker and the other half by multiple talkers. Results revealed that autistic participants’ sensitivity scores to accurately-spotted target words did not differ to those
of non-autistic participants, regardless of whether they were spoken by a single or multiple talkers. As expected, the non-autistic group showed the well-established processing cost associated with talker
variability (e.g., slower response times). Remarkably, autistic listeners’ response times did not differ across single- or multi-talker conditions, indicating they did not show perceptual processing costs
when accommodating talker variability. The present findings have implications for theories of autistic perception and speech and language processing.

Abstract

In an earlier study, it was shown that listeners can use prosodic cues that predict where sentence stress will fall; phoneme-monitoring RTs are faster when the preceding prosody indicates that the word bearing the target will be stressed. Two experiments which further investigate this effect are described. In the first, it is shown that the duration of the closure preceding the release of the target stop consonant burst does not affect the RT advantage for stressed words. In the second, it is shown that fundamental frequency variation is not a necessary component of the prosodic variation that produces the predicted-stress effect. It is argued that sentence processing involves a very flexible use of prosodic information.

Abstract

Reaction time to detect a phoneme target in a sentence was found to be faster when the word in which the target occurred formed part of the semantic focus of the sentence. Focus was determined by asking a question before the sentence; that part of the sentence which comprised the answer to the sentence was assumed to be focussed. This procedure made it possible to vary position offocus within the sentence while holding all acoustic aspects of the sentence itself constant. It is argued that sentence understanding is facilitated by rapid identification of focussed information. Since focussed words are usually accented, it is further argued that the active search for accented words demonstrated in previous research should be interpreted as a search for semantic focus.

Abstract

The order of some conjoined words is rigidly fixed (e.g. dribs and drabs/*drabs and dribs). Both phonetic and semantic factors can play a role in determining the fixed order. An experiment was conducted to test whether listerners’ reaction times for monitoring a predetermined phoneme are influenced by phonetic constraints on ordering. Two such constraints were investigated: monosyllable-bissyllable and high-low vowel sequences. In English, conjoined words occur in such sequences with much greater frequency than their converses, other factors being equal. Reaction times were significantly shorter for phoneme monitoring in monosyllable-bisyllable sequences than in bisyllable- monosyllable sequences. However, reaction times were not significantly different for high-low vs. low-high vowel sequences.