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<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-a-hardware-computation</journal-id>
<journal-title-group>
<journal-title>Global Journal of Computer Science and Technology - A: Hardware &amp; Computation</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
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<article-id pub-id-type="publisher-id">76436</article-id>
<title-group>
<article-title>Verification of Bangla Sentence Structure using N-Gram</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Khan</surname><given-names>Nur Hossain</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
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<aff id="aff1">BANGLADESH, Islamic University, Kushtia, Bangladesh</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2014-01-15">
<day>15</day>
<month>01</month>
<year>2014</year>
</pub-date>
<volume>14</volume>
<issue>A1</issue>
<fpage>1</fpage>
<lpage>5</lpage>
<abstract><p>Statistical N-gram language modeling is used in many domains like spelling and syntactic verification, speech recognition, machine translation, character recognition and like others. This paper describes a system for sentence structure verification based on Ngram modeling of Bangla. An experimental corpus containing one million word tokens was used to train the system. The corpus was a part of the BdNC01 corpus, created in the SIPL lab. of Islamic university. Collecting several sample text from different newspapers, the system was tested by 1000 correct and another 1000 incorrect sentences. The system has successfully identified the structural validity of test sentences at a rate of 93%. This paper also describes the limitations of our system with possible solutions.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>N-gram</kwd>
<kwd>sentence structure</kwd>
<kwd>corpus</kwd>
<kwd>witten-bell smoothing</kwd>
<kwd>word error.</kwd>
</kwd-group>
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<title>Full Text</title>
<p>Statistical N-gram language modeling is used in many domains like spelling and syntactic verification, speech recognition, machine translation, character recognition and like others. This paper describes a system for sentence structure verification based on Ngram modeling of Bangla. An experimental corpus containing one million word tokens was used to train the system. The corpus was a part of the BdNC01 corpus, created in the SIPL lab. of Islamic university. Collecting several sample text from different newspapers, the system was tested by 1000 correct and another 1000 incorrect sentences. The system has successfully identified the structural validity of test sentences at a rate of 93%. This paper also describes the limitations of our system with possible solutions.</p>
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