9,925 research outputs found

    Verb Bias in Mandarin Relative Clause Processing

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    Syntactic and semantic interplay during Chinese text processing.

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    by Tang Siu-Lam.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 48-54).Appendix in Chinese.Acknowledgements --- p.IAbstract --- p.IITable of Contents --- p.IIIAppendix --- p.IVIntroduction --- p.1Parsing Models --- p.3Possible Causes for the Discrepancies Observed in Past Studies --- p.7Language Specific Properties and Parsing --- p.13The Present Study --- p.15Experiment1 --- p.19Method --- p.22Results and Discussion --- p.25Experiment2 --- p.28Method --- p.30Results and Discussion --- p.30Experiment3 --- p.35Method --- p.38Results and Discussion --- p.38General Discussion --- p.45References --- p.43Appendix --- p.55"Instructions used in Experiments 1, 2, and3" --- p.5

    Contrastive grammar : a theory and practice handbook

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    En consonancia con los lineamientos del programa vigente de Gramática Contrastiva, materia incluida en el programa de estudios del Traductorado de Inglés de la Facultad de Lenguas, Universidad Nacional de Córdoba, el objetivo principal de Contrastive Grammar: A Theory and Practice Handbook es brindar a los estudiantes un manual que combine las gramáticas descriptivas del inglés y del español. No pretende ser una revisión completa de todas las diferencias lingüísticas existentes entre ambas lenguas: por el contrario, el objetivo del presente manual es combinar información teórica clave con prácticas variadas respecto de estructuras dispares que representan la fuente más frecuente de interferencia entre los dos sistemas.Fil: Gómez Calvillo, M. Natalia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Meehan, Patricia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Díaz, M. Josefina. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina.Fil: Rolfi, Laura. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina

    How Do People Process Ambiguous Strings

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    This article combines ambiguity phenomenon with Chinese word segmentation to observe how human being conduct language processing to clarify ambiguity between overlapping ambiguity and combination ambiguity. Artificial intelligence will easily missegment these two strings, while the study tries to introduce optimality theory to discover possible base of these two types of ambiguity comprehended by general people. According to the result, the key to clarify ambiguity is context, idiomaticity and word frequency

    Processing of Arabic Diacritical Marks: : Phonological-Syntactic Disambiguation of Homographic Verbs and Visual Crowding Effects

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    Diacritics convey vowel sounds in Arabic, allowing accurate word pronunciation. Mostly, modern Arabic is printed non-diacritised. Otherwise, diacritics appear either only on homographic words when not disambiguated by surrounding text or on all words as in religious or educational texts. In an eye tracking experiment we examined sentence processing in the absence of diacritics, and when diacritics were presented in either modes. Heterophonic-homographic target verbs that have different pronunciations in active and passive (e.g., برض /daraba/, hit; برض /doriba/, was hit) were embedded in temporarily ambiguous sentences where in the absence of diacritics, readers cannot be certain whether the verb was active or passive. Passive sentences were disambiguated by an extra word (e.g., ديب /bijad/, by the hand of). Our results show that readers processed the disambiguating diacritics when present only on the homographic verb. When disambiguating diacritics were absent, Arabic readers followed their parsing preference for active verb analysis, and garden path effects were observed. When reading fully diacritised sentences, readers incurred only a small cost, likely due to increased visual crowding, but did not extensively process the (mostly superfluous) diacritics, thus resulting in a lack of benefit from the disambiguating diacritics on the passive verb
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