Conference Papers (Centre for Research on Bangla Language Processing)
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Item Detecting flames and insults in text(BRAC University, 2008-12) Mahmud, Altaf; Ahmed, Kazi Zubair; Khan, MumitWhile the internet has become the leading source of information, it is also become the medium for flames, insults and other forms of abusive language, which add nothing to the quality of information available. A human reader can easily distinguish between what is information and what is a flame or any other form of abuse. It is however much more difficult for a language processor to do this automatically. This paper describes a new approach for an automated system to distinguish between information and personal attacks containing insulting or abusive expressions in a given document. In linguistics, insulting or abusive messages are viewed as an extreme subset of the subjective language because of its extreme nature. We create a set of rules to extract the semantic information of a given sentence from the general semantic structure of that sentence to separate information from abusive language.Item Example based English-Bengali machine translation using wordnet(BRAC University, 2009) Salm, Khan Md. Anwarus Salam; Khan, Mumit; Nishino, TetsuroIn this paper we propose an architecture of English-Bengali Example Based Machine Translation (EBMT) using WordNet. The proposed EBMT system has five steps: 1) Tagging 2) Parsing 3) Prepare the chunks of the sentence using sub-sentential EBMT 4) Using an efficient adapting scheme, match the sentence rule 5) Translate from Source Language (English) to Target Language (Bengali) in the chunk and generate with morphological analysis with the help of WordNet. Using the word senses given by the WordNet we can detect the ambiguity and improve the correctness of translation.Item N-gram based statistical grammar checker for Bangla and English(Center for research on Bangla language processing (CRBLP), BRAC University, 2006) Alam, Md. Jahangir; UzZaman, Naushad; Khan, MumitThis paper describes a statistical grammar checker, which considers the n-gram based analysis of words and POS tags to decide whether the sentence is grammatically correct or not. We employed this technique for both Bangla and English and also described limitation in our approach with possible solutions.Item JKimmo: A Multilingual computational mophology frame work for PC-KIMMO(BRAC University, 2006) Islam, Md. Zahurul; Khan, MumitMorphological analysis is of fundamental interest in computational linguistics and language processing. While there are established morphological analyzers for mostly Western and a few other languages using localized interfaces, the same cannot be said for Indic and other less-studied languages for which language processing is just beginning. There are three primary obstacles to computational morphological analysis of these less-studied languages: the generative rules that define the language morphology, the morphological processor, and the computational interface that a linguist can use to experiment with the generative rules. In this paper, we present JKimmo, a multilingual morphological open-source framework that uses the PC-KIMMO two-level morphological processor and provides a localized interface for Bangla morphological analysis. We then apply Jkimmo to Bangla computational morphology, demonstrating both its recognition and generation capabilities. Jkimmo’s internationalization (i18n) frame-work allows easy localization in other languages as well, using a property file for the interface definitions and a transliteration scheme for the analysis.Item Developing a computational grammar for Bengali using the HPSG formalism(BRAC University, 2006) Khan, Naira; Khan, MumitThis paper describes the first phase of developing a computational grammar for Bengali using the Head- Driven Phrase Structure Grammar (HPSG) formalism. The HPSG formalism is a highly developed framework that combines computational and psycholinguistic research to provide a tool with which the features particular to a language can be captured and simultaneously provide information about language universals i.e. linguistic phenomena common to diverse languages. The grammar is implemented on a Linguistic Knowledge Building (LKB) system that has both a syntactic and a semantic level. The system is a powerful tool that allows the user to build a parser along with a generator by using the formalism to code in linguistic rules through feature structures and feature unification. This paper provides a set of instructions for using the formulation of HPSG to parse as well as generate grammatical sentences of Bengali. This paper will enable linguists to interpret and formulate features and types with which Bengali or a structurally similar language can be coded in HPSG. It provides a stepping-stone towards the development of a full computational grammar for Bengali which will also provide useful information as a computational description for its sister languages.Item Comparison of Unigram, Bigram, HMM and Brill's POS tagging approaches for some South Asian languages(BRAC University, 2007) Hasan, Muhammad Fahim; Naushad UzZaman; Khan, MumitPart-of-Speech (POS) Tagging is a process that attaches each word in a sentence with a suitable tag from a given set of tags. POS Tagging is important in various areas of Natural Language Processing. Different methods of automating the process have been developed and employed for English and other Western languages. Some similar work, most of which utilize the stochastic approaches for POS Tagging has also been done in the same area for South Asian languages. We experimented with some of the widely-used approaches for POS Tagging on three South Asian languages, Bangla, Hindi and Telegu, using corpora of different sizes. We observed the performance of the approaches and found the Brill’s transformation based tagger’s performance to be superior to the other approaches in all of our experiments, though the use of this approach has been very limited until recently.