Publications

Displaying 101 - 112 of 112
  • Shattuck-Hufnagel, S., & Cutler, A. (1999). The prosody of speech error corrections revisited. In J. Ohala, Y. Hasegawa, M. Ohala, D. Granville, & A. Bailey (Eds.), Proceedings of the Fourteenth International Congress of Phonetic Sciences: Vol. 2 (pp. 1483-1486). Berkely: University of California.

    Abstract

    A corpus of digitized speech errors is used to compare the prosody of correction patterns for word-level vs. sound-level errors. Results for both peak F0 and perceived prosodic markedness confirm that speakers are more likely to mark corrections of word-level errors than corrections of sound-level errors, and that errors ambiguous between word-level and soundlevel (such as boat for moat) show correction patterns like those for sound level errors. This finding increases the plausibility of the claim that word-sound-ambiguous errors arise at the same level of processing as sound errors that do not form words.
  • Sidnell, J., & Stivers, T. (Eds.). (2005). Multimodal Interaction [Special Issue]. Semiotica, 156.
  • Sprenger, S. A., & Van Rijn, H. (2005). Clock time naming: Complexities of a simple task. In B. G. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th Annual Meeting of the Cognitive Science Society (pp. 2062-2067).
  • ten Bosch, L., & Scharenborg, O. (2005). ASR decoding in a computational model of human word recognition. In Interspeech'2005 - Eurospeech, 9th European Conference on Speech Communication and Technology (pp. 1241-1244). ISCA Archive.

    Abstract

    This paper investigates the interaction between acoustic scores and symbolic mismatch penalties in multi-pass speech decoding techniques that are based on the creation of a segment graph followed by a lexical search. The interaction between acoustic and symbolic mismatches determines to a large extent the structure of the search space of these multipass approaches. The background of this study is a recently developed computational model of human word recognition, called SpeM. SpeM is able to simulate human word recognition data and is built as a multi-pass speech decoder. Here, we focus on unravelling the structure of the search space that is used in SpeM and similar decoding strategies. Finally, we elaborate on the close relation between distances in this search space, and distance measures in search spaces that are based on a combination of acoustic and phonetic features.
  • Van Ooijen, B., Cutler, A., & Norris, D. (1991). Detection times for vowels versus consonants. In Eurospeech 91: Vol. 3 (pp. 1451-1454). Genova: Istituto Internazionale delle Comunicazioni.

    Abstract

    This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.
  • Van Geenhoven, V. (1999). A before-&-after picture of when-, before-, and after-clauses. In T. Matthews, & D. Strolovitch (Eds.), Proceedings of the 9th Semantics and Linguistic Theory Conference (pp. 283-315). Ithaca, NY, USA: Cornell University.
  • Van Valin Jr., R. D. (2000). Focus structure or abstract syntax? A role and reference grammar account of some ‘abstract’ syntactic phenomena. In Z. Estrada Fernández, & I. Barreras Aguilar (Eds.), Memorias del V Encuentro Internacional de Lingüística en el Noroeste: (2 v.) Estudios morfosintácticos (pp. 39-62). Hermosillo: Editorial Unison.
  • Vosse, T., & Kempen, G. (1991). A hybrid model of human sentence processing: Parsing right-branching, center-embedded and cross-serial dependencies. In M. Tomita (Ed.), Proceedings of the Second International Workshop on Parsing Technologies.
  • Walsh Dickey, L. (1999). Syllable count and Tzeltal segmental allomorphy. In J. Rennison, & K. Kühnhammer (Eds.), Phonologica 1996. Proceedings of the 8th International Phonology Meeting (pp. 323-334). Holland Academic Graphics.

    Abstract

    Tzeltal, a Mayan language spoken in southern Mexico, exhibits allo-morphy of an unusual type. The vowel quality of the perfective suffix is determined by the number of syllables in the stem to which it is attaching. This paper presents previously unpublished data of this allomorphy and demonstrates that a syllable-count analysis of the phenomenon is the proper one. This finding is put in a more general context of segment-prosody interaction in allomorphy.
  • 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.
  • Weber, A. (2000). Phonotactic and acoustic cues for word segmentation in English. In Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP 2000) (pp. 782-785).

    Abstract

    This study investigates the influence of both phonotactic and acoustic cues on the segmentation of spoken English. Listeners detected embedded English words in nonsense sequences (word spotting). Words aligned with phonotactic boundaries were easier to detect than words without such alignment. Acoustic cues to boundaries could also have signaled word boundaries, especially when word onsets lacked phonotactic alignment. However, only one of several durational boundary cues showed a marginally significant correlation with response times (RTs). The results suggest that word segmentation in English is influenced primarily by phonotactic constraints and only secondarily by acoustic aspects of the speech signal.
  • Weber, A. (2000). The role of phonotactics in the segmentation of native and non-native continuous speech. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP, Workshop on Spoken Word Access Processes. Nijmegen: MPI for Psycholinguistics.

    Abstract

    Previous research has shown that listeners make use of their knowledge of phonotactic constraints to segment speech into individual words. The present study investigates the influence of phonotactics when segmenting a non-native language. German and English listeners detected embedded English words in nonsense sequences. German listeners also had knowledge of English, but English listeners had no knowledge of German. Word onsets were either aligned with a syllable boundary or not, according to the phonotactics of the two languages. Words aligned with either German or English phonotactic boundaries were easier for German listeners to detect than words without such alignment. Responses of English listeners were influenced primarily by English phonotactic alignment. The results suggest that both native and non-native phonotactic constraints influence lexical segmentation of a non-native, but familiar, language.

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