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The Pennsylvania State University CiteSeerX Archives (36)
Naushad Uzzaman (5)
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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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