Anne Cutler †

Publications

Displaying 1 - 11 of 11
  • Cutler, A., & Bruggeman, L. (2013). Vocabulary structure and spoken-word recognition: Evidence from French reveals the source of embedding asymmetry. In Proceedings of INTERSPEECH: 14th Annual Conference of the International Speech Communication Association (pp. 2812-2816).

    Abstract

    Vocabularies contain hundreds of thousands of words built from only a handful of phonemes, so that inevitably longer words tend to contain shorter ones. In many languages (but not all) such embedded words occur more often word-initially than word-finally, and this asymmetry, if present, has farreaching consequences for spoken-word recognition. Prior research had ascribed the asymmetry to suffixing or to effects of stress (in particular, final syllables containing the vowel schwa). Analyses of the standard French vocabulary here reveal an effect of suffixing, as predicted by this account, and further analyses of an artificial variety of French reveal that extensive final schwa has an independent and additive effect in promoting the embedding asymmetry.
  • 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.
  • Allerhand, M., Butterfield, S., Cutler, A., & Patterson, R. (1992). Assessing syllable strength via an auditory model. In Proceedings of the Institute of Acoustics: Vol. 14 Part 6 (pp. 297-304). St. Albans, Herts: Institute of Acoustics.
  • Cutler, A., Kearns, R., Norris, D., & Scott, D. (1992). Listeners’ responses to extraneous signals coincident with English and French speech. In J. Pittam (Ed.), Proceedings of the 4th Australian International Conference on Speech Science and Technology (pp. 666-671). Canberra: Australian Speech Science and Technology Association.

    Abstract

    English and French listeners performed two tasks - click location and speeded click detection - with both English and French sentences, closely matched for syntactic and phonological structure. Clicks were located more accurately in open- than in closed-class words in both English and French; they were detected more rapidly in open- than in closed-class words in English, but not in French. The two listener groups produced the same pattern of responses, suggesting that higher-level linguistic processing was not involved in these tasks.
  • Cutler, A., & Robinson, T. (1992). Response time as a metric for comparison of speech recognition by humans and machines. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing: Vol. 1 (pp. 189-192). Alberta: University of Alberta.

    Abstract

    The performance of automatic speech recognition systems is usually assessed in terms of error rate. Human speech recognition produces few errors, but relative difficulty of processing can be assessed via response time techniques. We report the construction of a measure analogous to response time in a machine recognition system. This measure may be compared directly with human response times. We conducted a trial comparison of this type at the phoneme level, including both tense and lax vowels and a variety of consonant classes. The results suggested similarities between human and machine processing in the case of consonants, but differences in the case of vowels.
  • McQueen, J. M., & Cutler, A. (1992). Words within words: Lexical statistics and lexical access. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing: Vol. 1 (pp. 221-224). Alberta: University of Alberta.

    Abstract

    This paper presents lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.
  • Norris, D., Van Ooijen, B., & Cutler, A. (1992). Speeded detection of vowels and steady-state consonants. In J. Ohala, T. Neary, & B. Derwing (Eds.), Proceedings of the Second International Conference on Spoken Language Processing; Vol. 2 (pp. 1055-1058). Alberta: University of Alberta.

    Abstract

    We report two experiments in which vowels and steady-state consonants served as targets in a speeded detection task. In the first experiment, two vowels were compared with one voiced and once unvoiced fricative. Response times (RTs) to the vowels were longer than to the fricatives. The error rate was higher for the consonants. Consonants in word-final position produced the shortest RTs, For the vowels, RT correlated negatively with target duration. In the second experiment, the same two vowel targets were compared with two nasals. This time there was no significant difference in RTs, but the error rate was still significantly higher for the consonants. Error rate and length correlated negatively for the vowels only. We conclude that RT differences between phonemes are independent of vocalic or consonantal status. Instead, we argue that the process of phoneme detection reflects more finely grained differences in acoustic/articulatory structure within the phonemic repertoire.
  • 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.

Share this page