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Simple Search
Hits 1 – 6 of 6
1
Formality Style Transfer Within and Across Languages with Limited Supervision
Niu, Xing
. - 2019
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2
CROSS-LINGUISTIC TRANSFER OF SPELLING SKILLS IN SPANISH-SPEAKING ADULT ESL LEARNERS
Bai, Yu
. - 2016
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3
Ready for Transition: Factors that facilitate transfer to undergraduate engineering programs among Black African and American students
Berhane, Bruk
. - 2016
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4
PHONOLOGICAL PROCESSING UNIT TRANSFER: THE IMPACT OF FIRST LANGUAGE SYLLABLE STRUCTURE AND ITS IMPLICATIONS FOR PREFERRED SUBSYLLABIC DIVISION UNITS
Chen, Shih-wei
. - 2006
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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
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6
The relationship between phonological awareness and reading ability of Thai students in English and Thai in primary schools of Thailand
Wei, Youfu
. - 2005
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