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Hits 1 – 20 of 36

1	Bidirectional Bengali Script and Meetei Mayek Transliteration of Web Based Manipuri News Corpus
	Thoudam Doren Singh
	In: http://www.aclweb.org/anthology/W/W12/W12-5016.pdf (2012)
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2	How Difficult is it to Develop a Perfect Spell-checker? A Cross-linguistic Analysis through Complex Network Approach
	Monojit Choudhury; Markose Thomas; Animesh Mukherjee...
	In: http://arxiv.org/pdf/physics/0703198v1.pdf (2007)
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3	Unsupervised morphological parsing of Bengali. Language Resources and Evaluation
	Sajib Dasgupta; Vincent Ng
	In: http://www.hlt.utdallas.edu/~sajib/LRE.fdf (2006)
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4	A Comprehensive Bangla Spelling Checker
	Naushad Uzzaman; Mumit Khan
	In: http://www.naushadzaman.com/ComprehensiveSpeller.pdf (2006)
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5	A Double Metaphone Encoding for Bangla and its Application in Spelling Checker
	Naushad Uzzaman
	In: http://www.bracu.ac.bd/research/crblp/papers/DoubleMetaphoneSpell.pdf (2005)
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6	An MLP using Hough transform based fuzzy feature extraction for Bengali script recognition
	Shamik Sural; P.K. Das
	In: http://www.facweb.iitkgp.ernet.in/~shamik/papers/1999_PRL.pdf (1999)
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7	A global perspective on bilingualism and bilingual education. ERIC Digest. (ERIC Document Reproduction Service No. ED435168
	G. Richard Tucker; Carnegie Mellon University
	In: http://www.cal.org/resources/digest/digest_pdfs/9904-tucker-globalBE.pdf (1999)
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8	Bengali and Hindi to English Cross-language Text Retrieval under Limited Resources
	Debasis M; Ipan D; Mayank Gupta...
	In: http://www.clef-campaign.org/2007/working_notes/mandalCLEF2007.pdf
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9	A Faster Approach to Sort Unicode Represented Bengali Words
	Aamira Shabnam; Tapashee Tabassum
	In: http://www.ijcaonline.org/research/volume126/number11/shabnam-2015-ijca-906224.pdf
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10	THE DISTRIBUTION AND REALIZATION OF H TONES IN BENGALI
	Sameer Ud Dowla Khan
	In: http://www.linguistics.ucla.edu/faciliti/workpapph/106/The distribution and realization of H tones in Bengali.pdf
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11	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://wing.comp.nus.edu.sg/~antho/W/W13/W13-2233.pdf
	Abstract: Statistical machine translation (SMT) performance suffers when models are trained on only small amounts of parallel data. The learned models typically have both low accuracy (incorrect translations and feature scores) and low coverage (high out-of-vocabulary rates). In this work, we use an additional data resource, comparable corpora, to improve both. Beginning with a small bitext and corresponding phrase-based SMT model, we improve coverage by using bilingual lexicon induction techniques to learn new translations from comparable corpora. Then, we supplement the model’s feature space with translation scores estimated over comparable corpora in order to improve accuracy. We observe improvements between 0.5 and 1.7 BLEU translating Tamil, Telugu
	Keyword: and Urdu; Bengali; Hindi; Malayalam
	URL: http://wing.comp.nus.edu.sg/~antho/W/W13/W13-2233.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.8650
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12	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://www.cs.jhu.edu/~ccb/publications/combining-bilingual-and-comparable-corpora.pdf
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13	Bengali Question Classification: Towards Developing QA System ABSTRACT
	Somnath Banerjee; Sivaji Bandyopadhyay
	In: http://www.aclweb.org/anthology/W/W12/W12-5003.pdf
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14	SentiWordNet for Indian Languages
	Amitava Das; Sivaji B
	In: http://aclweb.org/anthology-new/W/W10/W10-3208.pdf
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15	Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
	Ann Irvine; Chris Callison-burch
	In: http://www.cs.jhu.edu/~anni/papers/irvineCCB_WMT13.pdf
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16	History (forward n-gram) or Future (backward n-gram)? Which model to consider for n-gram analysis in Bangla?
	Naira Khan; Md. Tarek Habib; Md. Jahangir Alam...
	In: http://www.naushadzaman.com/iccit06_backwardn-gram.pdf
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17	GOBINDA KOLE
	Pabitra Mitra
	In: http://www.facweb.iitkgp.ernet.in/~pabitra/paper/stemmer.pdf
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18	Analysis of Bangla Root Word for Universal Networking Language (UNL)
	Aloke Kumar Saha; M. F Mridha; Jugal Krishna Das
	In: http://research.ijcaonline.org/volume89/number17/pxc3894576.pdf
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19	Overview of Stemming Algorithms for Indian and Non-Indian Languages
	Dalwadi Bijal; Suthar Sanket
	In: http://ijcsit.com/docs/Volume+5/vol5issue02/ijcsit2014050241.pdf
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20	The akshara languages:
	In: http://www.york.ac.uk/media/psychology/crl/documents/sonalipapers/the akshara languages (Chapter 16 proofs).pdf
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