Displaying 101 - 105 of 105
-
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 Putten, S. (2013). The meaning of the Avatime additive particle tsye. In M. Balbach, L. Benz, S. Genzel, M. Grubic, A. Renans, S. Schalowski, M. Stegenwallner, & A. Zeldes (
Eds. ), Information structure: Empirical perspectives on theory (pp. 55-74). Potsdam: Universitätsverlag Potsdam. Retrieved from http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:de:kobv:517-opus-64804. -
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. -
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.
Share this page