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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. -
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.
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