282 research outputs found

    Chart-driven Connectionist Categorial Parsing of Spoken Korean

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    While most of the speech and natural language systems which were developed for English and other Indo-European languages neglect the morphological processing and integrate speech and natural language at the word level, for the agglutinative languages such as Korean and Japanese, the morphological processing plays a major role in the language processing since these languages have very complex morphological phenomena and relatively simple syntactic functionality. Obviously degenerated morphological processing limits the usable vocabulary size for the system and word-level dictionary results in exponential explosion in the number of dictionary entries. For the agglutinative languages, we need sub-word level integration which leaves rooms for general morphological processing. In this paper, we developed a phoneme-level integration model of speech and linguistic processings through general morphological analysis for agglutinative languages and a efficient parsing scheme for that integration. Korean is modeled lexically based on the categorial grammar formalism with unordered argument and suppressed category extensions, and chart-driven connectionist parsing method is introduced.Comment: 6 pages, Postscript file, Proceedings of ICCPOL'9

    Mixed-effects models for GAW18 longitudinal blood pressure data

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    In this paper, we propose two mixed-effects models for Genetic Analysis Workshop 18 (GAW18) longitudinal blood pressure data. The first method extends EMMA, an efficient mixed-model association-mapping algorithm. EMMA corrects for population structure and genetic relatedness using a kinship similarity matrix. We replace the kinship similarity matrix in EMMA with an estimated correlation matrix for modeling the dependence structure of repeated measurements. Our second approach is a Bayesian multiple association-mapping algorithm based on a mixed-effects model with a built-in variable selection feature. It models multiple single-nucleotide polymorphisms (SNPs) simultaneously and allows for SNP-SNP interactions and SNP-environment interactions. We applied these two methods to the longitudinal systolic blood pressure (SBP) and diastolic blood pressure (DBP) data from GAW18. The extended EMMA method identified a single SNP on Chr5:75506197 (p-value = 4.67 × 10(−7)) for SBP and three SNPs on Chr3:23715851 (p-value = 9.00 × 10(−8)), Chr 17:54834217 (p-value = 1.98 × 10(−7)), and Chr21:18744081 (p-value = 4.95 × 10(−7)) for DBP. The Bayesian method identified several additional SNPs on Chr1:17876090 (Bayes factor [BF] = 102), Chr3:197469358 (BF = 69), Chr15:87675666 (BF = 43), and Chr19:41642807 (BF = 33) for SBP. Furthermore, for SBP, we found a single SNP on Chr3:197469358 (BF = 69) that has a strong interaction with age. We further evaluated the performances of the proposed methods by simulations

    Word Recognition During Reading

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    Four eye-tracking experiments were conducted to understand how sentential context and lexical factors affect word recognition during reading. Experiment 1 examined whether readers use preceding sentential context to pre-activate a specific word and whether any processing cost is found when the prediction is wrong. The results showed that readers obtain a processing benefit when the target word was expected based on a strongly constraining context, whereas they experienced a processing cost when the target word was not the expected one even though it was semantically plausible into the context. Experiment 2 investigated how word recognition is influenced by prior activation of lexical information due to word repetition within a sentence. The result showed that gaze duration on a target word with many neighbor words was shorter relative to a target word with few neighbors but only when the target word was repeated; when the target word was not repeated gaze duration did not differ as a function of neighborhood size. This interaction indicates that word recognition at the orthographic level can be influenced by repetition-induced lexical activation. The null effect of the orthographic neighborhood size in the unrepeated condition was unexpected. Previous studies using the lexical-decision task have consistently shown a facilitative effect of orthographic neighborhood size. Therefore, Experiment 3 and 4 studied the role of neighborhood size during sentence reading with better controlled stimuli. The results showed an opposite pattern of results between gaze duration and word skipping such that gaze duration was longer when a word had many neighbors than when one had few neighbors, whereas skipping rates were higher in the many neighbor condition than in the few condition. The results indicate that having many neighbor words inhibits processes responsible for precise recognition of a word, but that it facilitates word skipping by increasing global lexical activity.Doctor of Philosoph
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