Publications

Displaying 201 - 205 of 205
  • 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.
  • Weterman, M. A. J., Wilbrink, M. J. M., Janssen, I. M., Janssen, H. A. P., Berg, E. v. d., Fisher, S. E., Craig, I., & Geurts van Kessel, A. H. M. (1996). Molecular cloning of the papillary renal cell carcinoma-associated translocation (X;1)(p11;q21) breakpoint. Cytogenetic and genome research, 75(1), 2-6. doi:10.1159/000134444.

    Abstract

    A combination of Southern blot analysis on a panel of tumor-derived somatic cell hybrids and fluorescence in situ hybridization techniques was used to map YACs, cosmids and DNA markers from the Xp11.2 region relative to the X chromosome breakpoint of the renal cell carcinoma-associated t(X;1)(p11;q21). The position of the breakpoint could be determined as follows: Xcen-OATL2-DXS146-DXS255-SYP-t(X;1)-TFE 3-OATL1-Xpter. Fluorescence in situ hybridization experiments using TFE3-containing YACs and cosmids revealed split signals indicating that the corresponding DNA inserts span the breakpoint region. Subsequent Southern blot analysis showed that a 2.3-kb EcoRI fragment which is present in all TFE3 cosmids identified, hybridizes to aberrant restriction fragments in three independent t(X;1)-positive renal cell carcinoma DNAs. The breakpoints in these tumors are not the same, but map within a region of approximately 6.5 kb. Through preparative gel electrophoresis an (X;1) chimaeric 4.4-kb EcoRI fragment could be isolated which encompasses the breakpoint region present on der(X). Preliminary characterization of this fragment revealed the presence of a 150-bp region with a strong homology to the 5' end of the mouse TFE3 cDNA in the X-chromosome part, and a 48-bp segment in the chromosome 1-derived part identical to the 5' end of a known EST (accession number R93849). These observations suggest that a fusion gene is formed between the two corresponding genes in t(X;1)(p11;q21)-positive papillary renal cell carcinomas.
  • 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.
  • Zavala, R. (2000). Multiple classifier systems in Akatek (Mayan). In G. Senft (Ed.), Systems of nominal classification (pp. 114-146). Cambridge University Press.

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