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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Formality Style Transfer Within and Across Languages with Limited Supervision Niu, Xing. - 2019 BASE Show details 2 CROSS-LINGUISTIC TRANSFER OF SPELLING SKILLS IN SPANISH-SPEAKING ADULT ESL LEARNERS Bai, Yu. - 2016 BASE Show details 3 Ready for Transition: Factors that facilitate transfer to undergraduate engineering programs among Black African and American students Berhane, Bruk. - 2016 BASE Show details 4 PHONOLOGICAL PROCESSING UNIT TRANSFER: THE IMPACT OF FIRST LANGUAGE SYLLABLE STRUCTURE AND ITS IMPLICATIONS FOR PREFERRED SUBSYLLABIC DIVISION UNITS Chen, Shih-wei. - 2006 BASE Show details 5 Rapid Resource Transfer for Multilingual Natural Language Processing Kolak, Okan. - 2005 Abstract: Until recently the focus of the Natural Language Processing (NLP) community has been on a handful of mostly European languages. However, the rapid changes taking place in the economic and political climate of the world precipitate a similar change to the relative importance given to various languages. The importance of rapidly acquiring NLP resources and computational capabilities in new languages is widely accepted. Statistical NLP models have a distinct advantage over rule-based methods in achieving this goal since they require far less manual labor. However, statistical methods require two fundamental resources for training: (1) online corpora (2) manual annotations. Creating these two resources can be as difficult as porting rule-based methods. This thesis demonstrates the feasibility of acquiring both corpora and annotations by exploiting existing resources for well-studied languages. Basic resources for new languages can be acquired in a rapid and cost-effective manner by utilizing existing resources cross-lingually. Currently, the most viable method of obtaining online corpora is converting existing printed text into electronic form using Optical Character Recognition (OCR). Unfortunately, a language that lacks online corpora most likely lacks OCR as well. We tackle this problem by taking an existing OCR system that was desgined for a specific language and using that OCR system for a language with a similar script. We present a generative OCR model that allows us to post-process output from a non-native OCR system to achieve accuracy close to, or better than, a native one. Furthermore, we show that the performance of a native or trained OCR system can be improved by the same method. Next, we demonstrate cross-utilization of annotations on treebanks. We present an algorithm that projects dependency trees across parallel corpora. We also show that a reasonable quality treebank can be generated by combining projection with a small amount of language-specific post-processing. The projected treebank allows us to train a parser that performs comparably to a parser trained on manually generated data. Keyword: Computer Science; Language; Linguistics; Multilingual Natural Language Processing (NLP); Optical Character Recognition (OCR) correction; Rapid resource transfer; Resource acquisition for NLP; Syntactic dependency projection URL: http://hdl.handle.net/1903/3182 BASE Hide details 6 The relationship between phonological awareness and reading ability of Thai students in English and Thai in primary schools of Thailand Wei, Youfu. - 2005 BASE Show details

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