Anne Cutler †

Publications

Displaying 1 - 19 of 19
  • Cutler, A., Weber, A., Smits, R., & Cooper, N. (2004). Patterns of English phoneme confusions by native and non-native listeners. Journal of the Acoustical Society of America, 116(6), 3668-3678. doi:10.1121/1.1810292.

    Abstract

    Native American English and non-native(Dutch)listeners identified either the consonant or the vowel in all possible American English CV and VC syllables. The syllables were embedded in multispeaker babble at three signal-to-noise ratios(0, 8, and 16 dB). The phoneme identification
    performance of the non-native listeners was less accurate than that of the native listeners. All listeners were adversely affected by noise. With these isolated syllables, initial segments were harder to identify than final segments. Crucially, the effects of language background and noise did not interact; the performance asymmetry between the native and non-native groups was not significantly different across signal-to-noise ratios. It is concluded that the frequently reported disproportionate difficulty of non-native listening under disadvantageous conditions is not due to a disproportionate increase in phoneme misidentifications.
  • Cutler, A. (2004). On spoken-word recognition in a second language. Newsletter, American Association of Teachers of Slavic and East European Languages, 47, 15-15.
  • Weber, A., & Cutler, A. (2004). Lexical competition in non-native spoken-word recognition. Journal of Memory and Language, 50(1), 1-25. doi:10.1016/S0749-596X(03)00105-0.

    Abstract

    Four eye-tracking experiments examined lexical competition in non-native spoken-word recognition. Dutch listeners hearing English fixated longer on distractor pictures with names containing vowels that Dutch listeners are likely to confuse with vowels in a target picture name (pencil, given target panda) than on less confusable distractors (beetle, given target bottle). English listeners showed no such viewing time difference. The confusability was asymmetric: given pencil as target, panda did not distract more than distinct competitors. Distractors with Dutch names phonologically related to English target names (deksel, ‘lid,’ given target desk) also received longer fixations than distractors with phonologically unrelated names. Again, English listeners showed no differential effect. With the materials translated into Dutch, Dutch listeners showed no activation of the English words (desk, given target deksel). The results motivate two conclusions: native phonemic categories capture second-language input even when stored representations maintain a second-language distinction; and lexical competition is greater for non-native than for native listeners.
  • Cutler, A., Norris, D., & McQueen, J. M. (1994). Modelling lexical access from continuous speech input. Dokkyo International Review, 7, 193-215.

    Abstract

    The recognition of speech involves the segmentation of continuous utterances into their component words. Cross-linguistic evidence is briefly reviewed which suggests that although there are language-specific solutions to this segmentation problem, they have one thing in common: they are all based on language rhythm. In English, segmentation is stress-based: strong syllables are postulated to be the onsets of words. Segmentation, however, can also be achieved by a process of competition between activated lexical hypotheses, as in the Shortlist model. A series of experiments is summarised showing that segmentation of continuous speech depends on both lexical competition and a metrically-guided procedure. In the final section, the implementation of metrical segmentation in the Shortlist model is described: the activation of lexical hypotheses matching strong syllables in the input is boosted and that of hypotheses mismatching strong syllables in the input is penalised.
  • Cutler, A., & Otake, T. (1994). Mora or phoneme? Further evidence for language-specific listening. Journal of Memory and Language, 33, 824-844. doi:10.1006/jmla.1994.1039.

    Abstract

    Japanese listeners detect speech sound targets which correspond precisely to a mora (a phonological unit which is the unit of rhythm in Japanese) more easily than targets which do not. English listeners detect medial vowel targets more slowly than consonants. Six phoneme detection experiments investigated these effects in both subject populations, presented with native- and foreign-language input. Japanese listeners produced faster and more accurate responses to moraic than to nonmoraic targets both in Japanese and, where possible, in English; English listeners responded differently. The detection disadvantage for medial vowels appeared with English listeners both in English and in Japanese; again, Japanese listeners responded differently. Some processing operations which listeners apply to speech input are language-specific; these language-specific procedures, appropriate for listening to input in the native language, may be applied to foreign-language input irrespective of whether they remain appropriate.
  • Cutler, A. (1994). The perception of rhythm in language. Cognition, 50, 79-81. doi:10.1016/0010-0277(94)90021-3.
  • McQueen, J. M., Norris, D., & Cutler, A. (1994). Competition in spoken word recognition: Spotting words in other words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 621-638.

    Abstract

    Although word boundaries are rarely clearly marked, listeners can rapidly recognize the individual words of spoken sentences. Some theories explain this in terms of competition between multiply activated lexical hypotheses; others invoke sensitivity to prosodic structure. We describe a connectionist model, SHORTLIST, in which recognition by activation and competition is successful with a realistically sized lexicon. Three experiments are then reported in which listeners detected real words embedded in nonsense strings, some of which were themselves the onsets of longer words. Effects both of competition between words and of prosodic structure were observed, suggesting that activation and competition alone are not sufficient to explain word recognition in continuous speech. However, the results can be accounted for by a version of SHORTLIST that is sensitive to prosodic structure.
  • Cutler, A., Mehler, J., Norris, D., & Segui, J. (1988). Limits on bilingualism [Letters to Nature]. Nature, 340, 229-230. doi:10.1038/340229a0.

    Abstract

    SPEECH, in any language, is continuous; speakers provide few reliable cues to the boundaries of words, phrases, or other meaningful units. To understand speech, listeners must divide the continuous speech stream into portions that correspond to such units. This segmentation process is so basic to human language comprehension that psycholinguists long assumed that all speakers would do it in the same way. In previous research1,2, however, we reported that segmentation routines can be language-specific: speakers of French process spoken words syllable by syllable, but speakers of English do not. French has relatively clear syllable boundaries and syllable-based timing patterns, whereas English has relatively unclear syllable boundaries and stress-based timing; thus syllabic segmentation would work more efficiently in the comprehension of French than in the comprehension of English. Our present study suggests that at this level of language processing, there are limits to bilingualism: a bilingual speaker has one and only one basic language.
  • Cutler, A., & Norris, D. (1988). The role of strong syllables in segmentation for lexical access. Journal of Experimental Psychology: Human Perception and Performance, 14, 113-121. doi:10.1037/0096-1523.14.1.113.

    Abstract

    A model of speech segmentation in a stress language is proposed, according to which the occurrence of a strong syllable triggers segmentation of the speech signal, whereas occurrence of a weak syllable does not trigger segmentation. We report experiments in which listeners detected words embedded in nonsense bisyllables more slowly when the bisyllable had two strong syllables than when it had a strong and a weak syllable; mint was detected more slowly in mintayve than in mintesh. According to our proposed model, this result is an effect of segmentation: When the second syllable is strong, it is segmented from the first syllable, and successful detection of the embedded word therefore requires assembly of speech material across a segmentation position. Speech recognition models involving phonemic or syllabic recoding, or based on strictly left-to-right processes, do not predict this result. It is argued that segmentation at strong syllables in continuous speech recognition serves the purpose of detecting the most efficient locations at which to initiate lexical access. (C) 1988 by the American Psychological Association
  • Henderson, L., Coltheart, M., Cutler, A., & Vincent, N. (1988). Preface. Linguistics, 26(4), 519-520. doi:10.1515/ling.1988.26.4.519.
  • Mehta, G., & Cutler, A. (1988). Detection of target phonemes in spontaneous and read speech. Language and Speech, 31, 135-156.

    Abstract

    Although spontaneous speech occurs more frequently in most listeners’ experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalize to the recognition of spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Response were, overall, equally fast in each speech mode. However analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than earlier targets, and targets preceded by long words were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claim from previous work that listeners pay great attention to prosodic information in the process of recognizing speech.
  • Norris, D., & Cutler, A. (1988). Speech recognition in French and English. MRC News, 39, 30-31.
  • Norris, D., & Cutler, A. (1988). The relative accessibility of phonemes and syllables. Perception and Psychophysics, 43, 541-550. Retrieved from http://www.psychonomic.org/search/view.cgi?id=8530.

    Abstract

    Previous research comparing detection times for syllables and for phonemes has consistently found that syllables are responded to faster than phonemes. This finding poses theoretical problems for strictly hierarchical models of speech recognition, in which smaller units should be able to be identified faster than larger units. However, inspection of the characteristics of previous experiments’stimuli reveals that subjects have been able to respond to syllables on the basis of only a partial analysis of the stimulus. In the present experiment, five groups of subjects listened to identical stimulus material. Phoneme and syllable monitoring under standard conditions was compared with monitoring under conditions in which near matches of target and stimulus occurred on no-response trials. In the latter case, when subjects were forced to analyze each stimulus fully, phonemes were detected faster than syllables.
  • Cutler, A. (1981). Degrees of transparency in word formation. Canadian Journal of Linguistics, 26, 73-77.
  • Cutler, A. (1981). Making up materials is a confounded nuisance, or: Will we able to run any psycholinguistic experiments at all in 1990? Cognition, 10, 65-70. doi:10.1016/0010-0277(81)90026-3.
  • Cutler, A., & Darwin, C. J. (1981). Phoneme-monitoring reaction time and preceding prosody: Effects of stop closure duration and of fundamental frequency. Perception and Psychophysics, 29, 217-224. Retrieved from http://www.psychonomic.org/search/view.cgi?id=12660.

    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.
  • Cutler, A. (1981). The reliability of speech error data. Linguistics, 19, 561-582.
  • Fodor, J. A., & Cutler, A. (1981). Semantic focus and sentence comprehension. Cognition, 7, 49-59. doi:10.1016/0010-0277(79)90010-6.

    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.
  • Garnham, A., Shillcock, R. C., Brown, G. D. A., Mill, A. I. D., & Cutler, A. (1981). Slips of the tongue in the London-Lund corpus of spontaneous conversation. Linguistics, 19, 805-817.

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