Anne Cutler †

Publications

Displaying 1 - 8 of 8
  • Alispahic, S., Pellicano, E., Cutler, A., & Antoniou, M. (2022). Auditory perceptual learning in autistic adults. Autism Research, 15(8), 1495-1507. doi:10.1002/aur.2778.

    Abstract

    The automatic retuning of phoneme categories to better adapt to the speech of a novel talker has been extensively documented across various (neurotypical) populations, including both adults and children. However, no studies have examined auditory perceptual learning effects in populations atypical in perceptual, social, and language processing for communication, such as populations with autism. Employing a classic lexically-guided perceptual learning paradigm, the present study investigated perceptual learning effects in Australian English autistic and non-autistic adults. The findings revealed that automatic attunement to existing phoneme categories was not activated in the autistic group in the same manner as for non-autistic control subjects. Specifically, autistic adults were able to both successfully discern lexical items and to categorize speech sounds; however, they did not show effects of perceptual retuning to talkers. These findings may have implications for the application of current sensory theories (e.g., Bayesian decision theory) to speech and language processing by autistic individuals.
    Lay Summary

    Lexically guided perceptual learning assists in the disambiguation of speech from a novel talker. The present study established that while Australian English autistic adult listeners were able to successfully discern lexical items and categorize speech sounds in their native language, perceptual flexibility in updating speaker-specific phonemic knowledge when exposed to a novel talker was not available. Implications for speech and language processing by autistic individuals as well as current sensory theories are discussed.

    Additional information

    data
  • Cutler, A., Ernestus, M., Warner, N., & Weber, A. (2022). Managing speech perception data sets. In B. McDonnell, E. Koller, & L. B. Collister (Eds.), The Open Handbook of Linguistic Data Management (pp. 565-573). Cambrdige, MA, USA: MIT Press. doi:10.7551/mitpress/12200.003.0055.
  • Ip, M. H. K., & Cutler, A. (2022). Juncture prosody across languages: Similar production but dissimilar perception. Laboratory Phonology, 13(1): 5. doi:10.16995/labphon.6464.

    Abstract

    How do speakers of languages with different intonation systems produce and perceive prosodic junctures in sentences with identical structural ambiguity? Native speakers of English and of Mandarin produced potentially ambiguous sentences with a prosodic juncture either earlier in the utterance (e.g., “He gave her # dog biscuits,” “他给她#狗饼干 ”), or later (e.g., “He gave her dog # biscuits,” “他给她狗 #饼干 ”). These productiondata showed that prosodic disambiguation is realised very similarly in the two languages, despite some differences in the degree to which individual juncture cues (e.g., pausing) were favoured. In perception experiments with a new disambiguation task, requiring speeded responses to select the correct meaning for structurally ambiguous sentences, language differences in disambiguation response time appeared: Mandarin speakers correctly disambiguated sentences with earlier juncture faster than those with later juncture, while English speakers showed the reverse. Mandarin-speakers with L2 English did not show their native-language response time pattern when they heard the English ambiguous sentences. Thus even with identical structural ambiguity and identically cued production, prosodic juncture perception across languages can differ.

    Additional information

    supplementary files
  • Liu, L., Yuan, C., Ong, J. H., Tuninetti, A., Antoniou, M., Cutler, A., & Escudero, P. (2022). Learning to perceive non-native tones via distributional training: Effects of task and acoustic cue weighting. Brain Sciences, 12(5): 559. doi:10.3390/brainsci12050559.

    Abstract

    As many distributional learning (DL) studies have shown, adult listeners can achieve discrimination of a difficult non-native contrast after a short repetitive exposure to tokens falling at the extremes of that contrast. Such studies have shown using behavioural methods that a short distributional training can induce perceptual learning of vowel and consonant contrasts. However, much less is known about the neurological correlates of DL, and few studies have examined non-native lexical tone contrasts. Here, Australian-English speakers underwent DL training on a Mandarin tone contrast using behavioural (discrimination, identification) and neural (oddball-EEG) tasks, with listeners hearing either a bimodal or a unimodal distribution. Behavioural results show that listeners learned to discriminate tones after both unimodal and bimodal training; while EEG responses revealed more learning for listeners exposed to the bimodal distribution. Thus, perceptual learning through exposure to brief sound distributions (a) extends to non-native tonal contrasts, and (b) is sensitive to task, phonetic distance, and acoustic cue-weighting. Our findings have implications for models of how auditory and phonetic constraints influence speech learning.

    Additional information

    supplementary material A-D
  • Cutler, A., & Norris, D. (2016). Bottoms up! How top-down pitfalls ensnare speech perception researchers too. Commentary on C. Firestone & B. Scholl: Cognition does not affect perception: Evaluating the evidence for 'top-down' effects. Behavioral and Brain Sciences, e236. doi:10.1017/S0140525X15002745.

    Abstract

    Not only can the pitfalls that Firestone & Scholl (F&S) identify be generalised across multiple studies within the field of visual perception, but also they have general application outside the field wherever perceptual and cognitive processing are compared. We call attention to the widespread susceptibility of research on the perception of speech to versions of the same pitfalls.
  • Norris, D., McQueen, J. M., & Cutler, A. (2016). Prediction, Bayesian inference and feedback in speech recognition. Language, Cognition and Neuroscience, 31(1), 4-18. doi:10.1080/23273798.2015.1081703.

    Abstract

    Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lexical processes as implemented in interactive-activation models (IAMs). We show that simple activation feedback does not actually improve speech recognition. However, other forms of feedback can be beneficial. In particular, feedback can enable the listener to adapt to changing input, and can potentially help the listener to recognise unusual input, or recognise speech in the presence of competing sounds. The common feature of these helpful forms of feedback is that they are all ways of optimising the performance of speech recognition using Bayesian inference. That is, listeners make predictions about speech because speech recognition is optimal in the sense captured in Bayesian models.
  • Cutler, A., & Fay, D. (1978). Introduction. In A. Cutler, & D. Fay (Eds.), [Annotated re-issue of R. Meringer and C. Mayer: Versprechen und Verlesen, 1895] (pp. ix-xl). Amsterdam: John Benjamins.
  • Cutler, A., & Cooper, W. E. (1978). Phoneme-monitoring in the context of different phonetic sequences. Journal of Phonetics, 6, 221-225.

    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.

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