Anne Cutler †

Publications

Displaying 1 - 9 of 9
  • 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.
  • Cutler, A., Murty, L., & Otake, T. (2003). Rhythmic similarity effects in non-native listening? In Proceedings of the 15th International Congress of Phonetic Sciences (PCPhS 2003) (pp. 329-332). Adelaide: Causal Productions.

    Abstract

    Listeners rely on native-language rhythm in segmenting speech; in different languages, stress-, syllable- or mora-based rhythm is exploited. This language-specificity affects listening to non- native speech, if native procedures are applied even though inefficient for the non-native language. However, speakers of two languages with similar rhythmic interpretation should segment their own and the other language similarly. This was observed to date only for related languages (English-Dutch; French-Spanish). We now report experiments in which Japanese listeners heard Telugu, a Dravidian language unrelated to Japanese, and Telugu listeners heard Japanese. In both cases detection of target sequences in speech was harder when target boundaries mismatched mora boundaries, exactly the pattern that Japanese listeners earlier exhibited with Japanese and other languages. These results suggest that Telugu and Japanese listeners use similar procedures in segmenting speech, and support the idea that languages fall into rhythmic classes, with aspects of phonological structure affecting listeners' speech segmentation.
  • Shi, R., Werker, J., & Cutler, A. (2003). Function words in early speech perception. In Proceedings of the 15th International Congress of Phonetic Sciences (pp. 3009-3012).

    Abstract

    Three experiments examined whether infants recognise functors in phrases, and whether their representations of functors are phonetically well specified. Eight- and 13- month-old English infants heard monosyllabic lexical words preceded by real functors (e.g., the, his) versus nonsense functors (e.g., kuh); the latter were minimally modified segmentally (but not prosodically) from real functors. Lexical words were constant across conditions; thus recognition of functors would appear as longer listening time to sequences with real functors. Eightmonth- olds' listening times to sequences with real versus nonsense functors did not significantly differ, suggesting that they did not recognise real functors, or functor representations lacked phonetic specification. However, 13-month-olds listened significantly longer to sequences with real functors. Thus, somewhere between 8 and 13 months of age infants learn familiar functors and represent them with segmental detail. We propose that accumulated frequency of functors in input in general passes a critical threshold during this time.
  • Van Ooijen, B., Cutler, A., & Berinetto, P. M. (1993). Click detection in Italian and English. In Eurospeech 93: Vol. 1 (pp. 681-684). Berlin: ESCA.

    Abstract

    We report four experiments in which English and Italian monolinguals detected clicks in continous speech in their native language. Two of the experiments used an off-line location task, and two used an on-line reaction time task. Despite there being large differences between English and Italian with respect to rhythmic characteristics, very similar response patterns were found for the two language groups. It is concluded that the process of click detection operates independently from language-specific differences in perceptual processing at the sublexical level.
  • Young, D., Altmann, G. T., Cutler, A., & Norris, D. (1993). Metrical structure and the perception of time-compressed speech. In Eurospeech 93: Vol. 2 (pp. 771-774).

    Abstract

    In the absence of explicitly marked cues to word boundaries, listeners tend to segment spoken English at the onset of strong syllables. This may suggest that under difficult listening conditions, speech should be easier to recognize where strong syllables are word-initial. We report two experiments in which listeners were presented with sentences which had been time-compressed to make listening difficult. The first study contrasted sentences in which all content words began with strong syllables with sentences in which all content words began with weak syllables. The intelligibility of the two groups of sentences did not differ significantly. Apparent rhythmic effects in the results prompted a second experiment; however, no significant effects of systematic rhythmic manipulation were observed. In both experiments, the strongest predictor of intelligibility was the rated plausibility of the sentences. We conclude that listeners' recognition responses to time-compressed speech may be strongly subject to experiential bias; effects of rhythmic structure are most likely to show up also as bias effects.
  • Butterfield, S., & Cutler, A. (1988). Segmentation errors by human listeners: Evidence for a prosodic segmentation strategy. In W. Ainsworth, & J. Holmes (Eds.), Proceedings of SPEECH ’88: Seventh Symposium of the Federation of Acoustic Societies of Europe: Vol. 3 (pp. 827-833). Edinburgh: Institute of Acoustics.
  • Cutler, A. (1983). Semantics, syntax and sentence accent. In M. Van den Broecke, & A. Cohen (Eds.), Proceedings of the Tenth International Congress of Phonetic Sciences (pp. 85-91). Dordrecht: Foris.
  • Scott, D. R., & Cutler, A. (1982). Segmental cues to syntactic structure. In Proceedings of the Institute of Acoustics 'Spectral Analysis and its Use in Underwater Acoustics' (pp. E3.1-E3.4). London: Institute of Acoustics.

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