Publications

Displaying 101 - 116 of 116
  • Sumer, B., Grabitz, C., & Küntay, A. (2017). Early produced signs are iconic: Evidence from Turkish Sign Language. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci 2017) (pp. 3273-3278). Austin, TX: Cognitive Science Society.

    Abstract

    Motivated form-meaning mappings are pervasive in sign languages, and iconicity has recently been shown to facilitate sign learning from early on. This study investigated the role of iconicity for language acquisition in Turkish Sign Language (TID). Participants were 43 signing children (aged 10 to 45 months) of deaf parents. Sign production ability was recorded using the adapted version of MacArthur Bates Communicative Developmental Inventory (CDI) consisting of 500 items for TID. Iconicity and familiarity ratings for a subset of 104 signs were available. Our results revealed that the iconicity of a sign was positively correlated with the percentage of children producing a sign and that iconicity significantly predicted the percentage of children producing a sign, independent of familiarity or phonological complexity. Our results are consistent with previous findings on sign language acquisition and provide further support for the facilitating effect of iconic form-meaning mappings in sign learning.
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2017). The recognition of compounds: A computational account. In Proceedings of Interspeech 2017 (pp. 1158-1162). doi:10.21437/Interspeech.2017-1048.

    Abstract

    This paper investigates the processes in comprehending spoken noun-noun compounds, using data from the BALDEY database. BALDEY contains lexicality judgments and reaction times (RTs) for Dutch stimuli for which also linguistic information is included. Two different approaches are combined. The first is based on regression by Dynamic Survival Analysis, which models decisions and RTs as a consequence of the fact that a cumulative density function exceeds some threshold. The parameters of that function are estimated from the observed RT data. The second approach is based on DIANA, a process-oriented computational model of human word comprehension, which simulates the comprehension process with the acoustic stimulus as input. DIANA gives the identity and the number of the word candidates that are activated at each 10 ms time step.

    Both approaches show how the processes involved in comprehending compounds change during a stimulus. Survival Analysis shows that the impact of word duration varies during the course of a stimulus. The density of word and non-word hypotheses in DIANA shows a corresponding pattern with different regimes. We show how the approaches complement each other, and discuss additional ways in which data and process models can be combined.
  • Tsoukala, C., Frank, S. L., & Broersma, M. (2017). “He's pregnant": Simulating the confusing case of gender pronoun errors in L2 English. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (pp. 3392-3397). Austin, TX, USA: Cognitive Science Society.

    Abstract

    Even advanced Spanish speakers of second language English tend to confuse the pronouns ‘he’ and ‘she’, often without even noticing their mistake (Lahoz, 1991). A study by AntónMéndez (2010) has indicated that a possible reason for this error is the fact that Spanish is a pro-drop language. In order to test this hypothesis, we used an extension of Dual-path (Chang, 2002), a computational cognitive model of sentence production, to simulate two models of bilingual speech production of second language English. One model had Spanish (ES) as a native language, whereas the other learned a Spanish-like language that used the pronoun at all times (non-pro-drop Spanish, NPD_ES). When tested on L2 English sentences, the bilingual pro-drop Spanish model produced significantly more gender pronoun errors, confirming that pronoun dropping could indeed be responsible for the gender confusion in natural language use as well.
  • De Vaan, L. (2017). Mental representations of Dutch regular morphologically complex neologisms. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Van Dooren, A., Dieuleveut, A., Cournane, A., & Hacquard, V. (2017). Learning what must and can must and can mean. In A. Cremers, T. Van Gessel, & F. Roelofsen (Eds.), Proceedings of the 21st Amsterdam Colloquium (pp. 225-234). Amsterdam: ILLC.

    Abstract

    This corpus study investigates how children figure out that functional modals
    like must can express various flavors of modality. We examine how modality is
    expressed in speech to and by children, and find that the way speakers use
    modals may obscure their polysemy. Yet, children eventually figure it out. Our
    results suggest that some do before age 3. We show that while root and
    epistemic flavors are not equally well-represented in the input, there are robust
    correlations between flavor and aspect, which learners could exploit to discover
    modal polysemy.
  • Van Dooren, A. (2017). Dutch must more structure. In A. Lamont, & K. Tetzloff (Eds.), NELS 47: Proceedings of the Forty-Seventh Annual Meeting of the North East Linguistic Society (pp. 165-175). Amherst: GLSA.
  • 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 Donselaar, W., Kuijpers, C., & Cutler, A. (1996). How do Dutch listeners process words with epenthetic schwa? In H. T. Bunnell (Ed.), Proceedings of the Fourth International Conference on Spoken Language Processing: Vol. 1 (pp. 149-152). New York: Institute of Electrical and Electronics Engineers.

    Abstract

    Dutch words with certain final consonant clusters are subject to optional schwa epenthesis. The present research aimed at investigating how Dutch listeners deal with this type of phonological variation. By means of syllable monitoring experiments, it was investigated whether Dutch listeners process words with epenthetic schwa (e.g., ’balluk’) as bisyllabic words or rather as monosyllabic words. Real words (e.g., ’balk’, ’balluk’) and pseudowords (e.g., ’golk’, ’golluk’) were compared, to examine effects of lexical representation. No difference was found between monitoring times for BAL targets in ’balluk’ carriers as compared to ’balk’ carriers. This suggests that words with epenthetic schwa are not processed as bisyllabic words. The effects for the pseudo-words paralleled those for the real words, which suggests that they are not due to lexical representation but rather to the application of phonological rules.
  • Van Berkum, J. J. A. (1996). The psycholinguistics of grammatical gender: Studies in language comprehension and production. PhD Thesis, University of Nijmegen.
  • Vanlangendonck, F. (2017). Finding common ground: On the neural mechanisms of communicative language production. PhD Thesis, Radboud University, Nijmegen.
  • 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.
  • Weber, A. (1998). Listening to nonnative language which violates native assimilation rules. In D. Duez (Ed.), Proceedings of the European Scientific Communication Association workshop: Sound patterns of Spontaneous Speech (pp. 101-104).

    Abstract

    Recent studies using phoneme detection tasks have shown that spoken-language processing is neither facilitated nor interfered with by optional assimilation, but is inhibited by violation of obligatory assimilation. Interpretation of these results depends on an assessment of their generality, specifically, whether they also obtain when listeners are processing nonnative language. Two separate experiments are presented in which native listeners of German and native listeners of Dutch had to detect a target fricative in legal monosyllabic Dutch nonwords. All of the nonwords were correct realisations in standard Dutch. For German listeners, however, half of the nonwords contained phoneme strings which violate the German fricative assimilation rule. Whereas the Dutch listeners showed no significant effects, German listeners detected the target fricative faster when the German fricative assimilation was violated than when no violation occurred. The results might suggest that violation of assimilation rules does not have to make processing more difficult per se.
  • Wittek, A. (1998). Learning verb meaning via adverbial modification: Change-of-state verbs in German and the adverb "wieder" again. In A. Greenhill, M. Hughes, H. Littlefield, & H. Walsh (Eds.), Proceedings of the 22nd Annual Boston University Conference on Language Development (pp. 779-790). Somerville, MA: Cascadilla Press.
  • Wittenburg, P., van Kuijk, D., & Dijkstra, T. (1996). Modeling human word recognition with sequences of artificial neurons. In C. von der Malsburg, W. von Seelen, J. C. Vorbrüggen, & B. Sendhoff (Eds.), Artificial Neural Networks — ICANN 96. 1996 International Conference Bochum, Germany, July 16–19, 1996 Proceedings (pp. 347-352). Berlin: Springer.

    Abstract

    A new psycholinguistically motivated and neural network based model of human word recognition is presented. In contrast to earlier models it uses real speech as input. At the word layer acoustical and temporal information is stored by sequences of connected sensory neurons which pass on sensor potentials to a word neuron. In experiments with a small lexicon which includes groups of very similar word forms, the model meets high standards with respect to word recognition and simulates a number of wellknown psycholinguistical effects.
  • Zhang, Y., & Yu, C. (2017). How misleading cues influence referential uncertainty in statistical cross-situational learning. In M. LaMendola, & J. Scott (Eds.), Proceedings of the 41st Annual Boston University Conference on Language Development (BUCLD 41) (pp. 820-833). Boston, MA: Cascadilla Press.
  • De Zubicaray, G., & Fisher, S. E. (Eds.). (2017). Genes, brain and language [Special Issue]. Brain and Language, 172.

Share this page