Anne Cutler †

Publications

Displaying 1 - 10 of 10
  • Cutler, A., Andics, A., & Fang, Z. (2011). Inter-dependent categorization of voices and segments. In W.-S. Lee, & E. Zee (Eds.), Proceedings of the 17th International Congress of Phonetic Sciences [ICPhS 2011] (pp. 552-555). Hong Kong: Department of Chinese, Translation and Linguistics, City University of Hong Kong.

    Abstract

    Listeners performed speeded two-alternative choice between two unfamiliar and relatively similar voices or between two phonetically close segments, in VC syllables. For each decision type (segment, voice), the non-target dimension (voice, segment) either was constant, or varied across four alternatives. Responses were always slower when a non-target dimension varied than when it did not, but the effect of phonetic variation on voice identity decision was stronger than that of voice variation on phonetic identity decision. Cues to voice and segment identity in speech are processed inter-dependently, but hard categorization decisions about voices draw on, and are hence sensitive to, segmental information.
  • Tuinman, A., Mitterer, H., & Cutler, A. (2011). The efficiency of cross-dialectal word recognition. In Proceedings of the 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), Florence, Italy (pp. 153-156).

    Abstract

    Dialects of the same language can differ in the casual speech processes they allow; e.g., British English allows the insertion of [r] at word boundaries in sequences such as saw ice, while American English does not. In two speeded word recognition experiments, American listeners heard such British English sequences; in contrast to non-native listeners, they accurately perceived intended vowel-initial words even with intrusive [r]. Thus despite input mismatches, cross-dialectal word recognition benefits from the full power of native-language processing.
  • Wagner, M., Tran, D., Togneri, R., Rose, P., Powers, D., Onslow, M., Loakes, D., Lewis, T., Kuratate, T., Kinoshita, Y., Kemp, N., Ishihara, S., Ingram, J., Hajek, J., Grayden, D., Göcke, R., Fletcher, J., Estival, D., Epps, J., Dale, R. and 11 moreWagner, M., Tran, D., Togneri, R., Rose, P., Powers, D., Onslow, M., Loakes, D., Lewis, T., Kuratate, T., Kinoshita, Y., Kemp, N., Ishihara, S., Ingram, J., Hajek, J., Grayden, D., Göcke, R., Fletcher, J., Estival, D., Epps, J., Dale, R., Cutler, A., Cox, F., Chetty, G., Cassidy, S., Butcher, A., Burnham, D., Bird, S., Best, C., Bennamoun, M., Arciuli, J., & Ambikairajah, E. (2011). The Big Australian Speech Corpus (The Big ASC). In M. Tabain, J. Fletcher, D. Grayden, J. Hajek, & A. Butcher (Eds.), Proceedings of the Thirteenth Australasian International Conference on Speech Science and Technology (pp. 166-170). Melbourne: ASSTA.
  • Burnham, D., Ambikairajah, E., Arciuli, J., Bennamoun, M., Best, C. T., Bird, S., Butcher, A. R., Cassidy, S., Chetty, G., Cox, F. M., Cutler, A., Dale, R., Epps, J. R., Fletcher, J. M., Goecke, R., Grayden, D. B., Hajek, J. T., Ingram, J. C., Ishihara, S., Kemp, N. and 10 moreBurnham, D., Ambikairajah, E., Arciuli, J., Bennamoun, M., Best, C. T., Bird, S., Butcher, A. R., Cassidy, S., Chetty, G., Cox, F. M., Cutler, A., Dale, R., Epps, J. R., Fletcher, J. M., Goecke, R., Grayden, D. B., Hajek, J. T., Ingram, J. C., Ishihara, S., Kemp, N., Kinoshita, Y., Kuratate, T., Lewis, T. W., Loakes, D. E., Onslow, M., Powers, D. M., Rose, P., Togneri, R., Tran, D., & Wagner, M. (2009). A blueprint for a comprehensive Australian English auditory-visual speech corpus. In M. Haugh, K. Burridge, J. Mulder, & P. Peters (Eds.), Selected proceedings of the 2008 HCSNet Workshop on Designing the Australian National Corpus (pp. 96-107). Somerville, MA: Cascadilla Proceedings Project.

    Abstract

    Large auditory-visual (AV) speech corpora are the grist of modern research in speech science, but no such corpus exists for Australian English. This is unfortunate, for speech science is the brains behind speech technology and applications such as text-to-speech (TTS) synthesis, automatic speech recognition (ASR), speaker recognition and forensic identification, talking heads, and hearing prostheses. Advances in these research areas in Australia require a large corpus of Australian English. Here the authors describe a blueprint for building the Big Australian Speech Corpus (the Big ASC), a corpus of over 1,100 speakers from urban and rural Australia, including speakers of non-indigenous, indigenous, ethnocultural, and disordered forms of Australian English, each of whom would be sampled on three occasions in a range of speech tasks designed by the researchers who would be using the corpus.
  • Cutler, A., Davis, C., & Kim, J. (2009). Non-automaticity of use of orthographic knowledge in phoneme evaluation. In Proceedings of the 10th Annual Conference of the International Speech Communication Association (Interspeech 2009) (pp. 380-383). Causal Productions Pty Ltd.

    Abstract

    Two phoneme goodness rating experiments addressed the role of orthographic knowledge in the evaluation of speech sounds. Ratings for the best tokens of /s/ were higher in words spelled with S (e.g., bless) than in words where /s/ was spelled with C (e.g., voice). This difference did not appear for analogous nonwords for which every lexical neighbour had either S or C spelling (pless, floice). Models of phonemic processing incorporating obligatory influence of lexical information in phonemic processing cannot explain this dissociation; the data are consistent with models in which phonemic decisions are not subject to necessary top-down lexical influence.
  • Braun, B., Lemhöfer, K., & Cutler, A. (2008). English word stress as produced by English and Dutch speakers: The role of segmental and suprasegmental differences. In Proceedings of Interspeech 2008 (pp. 1953-1953).

    Abstract

    It has been claimed that Dutch listeners use suprasegmental cues (duration, spectral tilt) more than English listeners in distinguishing English word stress. We tested whether this asymmetry also holds in production, comparing the realization of English word stress by native English speakers and Dutch speakers. Results confirmed that English speakers centralize unstressed vowels more, while Dutch speakers of English make more use of suprasegmental differences.
  • Braun, B., Tagliapietra, L., & Cutler, A. (2008). Contrastive utterances make alternatives salient: Cross-modal priming evidence. In Proceedings of Interspeech 2008 (pp. 69-69).

    Abstract

    Sentences with contrastive intonation are assumed to presuppose contextual alternatives to the accented elements. Two cross-modal priming experiments tested in Dutch whether such contextual alternatives are automatically available to listeners. Contrastive associates – but not non- contrastive associates - were facilitated only when primes were produced in sentences with contrastive intonation, indicating that contrastive intonation makes unmentioned contextual alternatives immediately available. Possibly, contrastive contours trigger a “presupposition resolution mechanism” by which these alternatives become salient.
  • Cutler, A., McQueen, J. M., Butterfield, S., & Norris, D. (2008). Prelexically-driven perceptual retuning of phoneme boundaries. In Proceedings of Interspeech 2008 (pp. 2056-2056).

    Abstract

    Listeners heard an ambiguous /f-s/ in nonword contexts where only one of /f/ or /s/ was legal (e.g., frul/*srul or *fnud/snud). In later categorisation of a phonetic continuum from /f/ to /s/, their category boundaries had shifted; hearing -rul led to expanded /f/ categories, -nud expanded /s/. Thus phonotactic sequence information alone induces perceptual retuning of phoneme category boundaries; lexical access is not required.
  • Koster, M., & Cutler, A. (1997). Segmental and suprasegmental contributions to spoken-word recognition in Dutch. In Proceedings of EUROSPEECH 97 (pp. 2167-2170). Grenoble, France: ESCA.

    Abstract

    Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.
  • Pallier, C., Cutler, A., & Sebastian-Galles, N. (1997). Prosodic structure and phonetic processing: A cross-linguistic study. In Proceedings of EUROSPEECH 97 (pp. 2131-2134). Grenoble, France: ESCA.

    Abstract

    Dutch and Spanish differ in how predictable the stress pattern is as a function of the segmental content: it is correlated with syllable weight in Dutch but not in Spanish. In the present study, two experiments were run to compare the abilities of Dutch and Spanish speakers to separately process segmental and stress information. It was predicted that the Spanish speakers would have more difficulty focusing on the segments and ignoring the stress pattern than the Dutch speakers. The task was a speeded classification task on CVCV syllables, with blocks of trials in which the stress pattern could vary versus blocks in which it was fixed. First, we found interference due to stress variability in both languages, suggesting that the processing of segmental information cannot be performed independently of stress. Second, the effect was larger for Spanish than for Dutch, suggesting that that the degree of interference from stress variation may be partially mitigated by the predictability of stress placement in the language.

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