Anne Cutler

Publications

Displaying 1 - 14 of 14
  • Bruggeman, L., & Cutler, A. (2019). The dynamics of lexical activation and competition in bilinguals’ first versus second language. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1342-1346). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Speech input causes listeners to activate multiple candidate words which then compete with one another. These include onset competitors, that share a beginning (bumper, butter), but also, counterintuitively, rhyme competitors, sharing an ending (bumper, jumper). In L1, competition is typically stronger for onset than for rhyme. In L2, onset competition has been attested but rhyme competition has heretofore remained largely unexamined. We assessed L1 (Dutch) and L2 (English) word recognition by the same late-bilingual individuals. In each language, eye gaze was recorded as listeners heard sentences and viewed sets of drawings: three unrelated, one depicting an onset or rhyme competitor of a word in the input. Activation patterns revealed substantial onset competition but no significant rhyme competition in either L1 or L2. Rhyme competition may thus be a “luxury” feature of maximally efficient listening, to be abandoned when resources are scarcer, as in listening by late bilinguals, in either language.
  • Cutler, A., Burchfield, A., & Antoniou, M. (2019). A criterial interlocutor tally for successful talker adaptation? In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1485-1489). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Part of the remarkable efficiency of listening is accommodation to unfamiliar talkers’ specific pronunciations by retuning of phonemic intercategory boundaries. Such retuning occurs in second (L2) as well as first language (L1); however, recent research with emigrés revealed successful adaptation in the environmental L2 but, unprecedentedly, not in L1 despite continuing L1 use. A possible explanation involving relative exposure to novel talkers is here tested in heritage language users with Mandarin as family L1 and English as environmental language. In English, exposure to an ambiguous sound in disambiguating word contexts prompted the expected adjustment of phonemic boundaries in subsequent categorisation. However, no adjustment occurred in Mandarin, again despite regular use. Participants reported highly asymmetric interlocutor counts in the two languages. We conclude that successful retuning ability requires regular exposure to novel talkers in the language in question, a criterion not met for the emigrés’ or for these heritage users’ L1.
  • Joo, H., Jang, J., Kim, S., Cho, T., & Cutler, A. (2019). Prosodic structural effects on coarticulatory vowel nasalization in Australian English in comparison to American English. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 835-839). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This study investigates effects of prosodic factors (prominence, boundary) on coarticulatory Vnasalization in Australian English (AusE) in CVN and NVC in comparison to those in American English (AmE). As in AmE, prominence was found to lengthen N, but to reduce V-nasalization, enhancing N’s nasality and V’s orality, respectively (paradigmatic contrast enhancement). But the prominence effect in CVN was more robust than that in AmE. Again similar to findings in AmE, boundary induced a reduction of N-duration and V-nasalization phrase-initially (syntagmatic contrast enhancement), and increased the nasality of both C and V phrasefinally. But AusE showed some differences in terms of the magnitude of V nasalization and N duration. The results suggest that the linguistic contrast enhancements underlie prosodic-structure modulation of coarticulatory V-nasalization in comparable ways across dialects, while the fine phonetic detail indicates that the phonetics-prosody interplay is internalized in the individual dialect’s phonetic grammar.
  • 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.
  • McQueen, J. M., Norris, D., & Cutler, A. (2001). Can lexical knowledge modulate prelexical representations over time? In R. Smits, J. Kingston, T. Neary, & R. Zondervan (Eds.), Proceedings of the workshop on Speech Recognition as Pattern Classification (SPRAAC) (pp. 145-150). Nijmegen: Max Planck Institute for Psycholinguistics.

    Abstract

    The results of a study on perceptual learning are reported. Dutch subjects made lexical decisions on a list of words and nonwords. Embedded in the list were either [f]- or [s]-final words in which the final fricative had been replaced by an ambiguous sound, midway between [f] and [s]. One group of listeners heard ambiguous [f]- final Dutch words like [kara?] (based on karaf, carafe) and unambiguous [s]-final words (e.g., karkas, carcase). A second group heard the reverse (e.g., ambiguous [karka?] and unambiguous karaf). After this training phase, listeners labelled ambiguous fricatives on an [f]- [s] continuum. The subjects who had heard [?] in [f]- final words categorised these fricatives as [f] reliably more often than those who had heard [?] in [s]-final words. These results suggest that speech recognition is dynamic: the system adjusts to the constraints of each particular listening situation. The lexicon can provide this adjustment process with a training signal.
  • Moore, R. K., & Cutler, A. (2001). Constraints on theories of human vs. machine recognition of speech. In R. Smits, J. Kingston, T. Neary, & R. Zondervan (Eds.), Proceedings of the workshop on Speech Recognition as Pattern Classification (SPRAAC) (pp. 145-150). Nijmegen: Max Planck Institute for Psycholinguistics.

    Abstract

    The central issues in the study of speech recognition by human listeners (HSR) and of automatic speech recognition (ASR) are clearly comparable; nevertheless the research communities that concern themselves with ASR and HSR are largely distinct. This paper compares the research objectives of the two fields, and attempts to draw informative lessons from one to the other.
  • Otake, T., & Cutler, A. (2001). Recognition of (almost) spoken words: Evidence from word play in Japanese. In P. Dalsgaard (Ed.), Proceedings of EUROSPEECH 2001 (pp. 465-468).

    Abstract

    Current models of spoken-word recognition assume automatic activation of multiple candidate words fully or partially compatible with the speech input. We propose that listeners make use of this concurrent activation in word play such as punning. Distortion in punning should ideally involve no more than a minimal contrastive deviation between two words, namely a phoneme. Moreover, we propose that this metric of similarity does not presuppose phonemic awareness on the part of the punster. We support these claims with an analysis of modern and traditional puns in Japanese (in which phonemic awareness in language users is not encouraged by alphabetic orthography). For both data sets, the results support the predictions. Punning draws on basic processes of spokenword recognition, common across languages.
  • Warner, N., Jongman, A., Mucke, D., & Cutler, A. (2001). The phonological status of schwa insertion in Dutch: An EMA study. In B. Maassen, W. Hulstijn, R. Kent, H. Peters, & P. v. Lieshout (Eds.), Speech motor control in normal and disordered speech: 4th International Speech Motor Conference (pp. 86-89). Nijmegen: Vantilt.

    Abstract

    Articulatory data are used to address the question of whether Dutch schwa insertion is a phonological or a phonetic process. By investigating tongue tip raising and dorsal lowering, we show that /l/ when it appears before inserted schwa is a light /l/, just as /l/ before an underlying schwa is, and unlike the dark /l/ before a consonant in non-insertion productions of the same words. The fact that inserted schwa can condition the light/dark /l/ alternation shows that schwa insertion involves the phonological insertion of a segment rather than phonetic adjustments to articulations.
  • 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.

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