N-GRAMS SOLUTION FOR ERROR DETECTION AND CORRECTION IN HINDI LANGUAGE

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Published: Aug 28, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i7.4364
Keywords:
Natural Language Processing, Real Word Error, Spell Checking, N Grams

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Shailza Kanwar
SLIET Longowal, Sangrur
Manoj Kumar Sachan
SLIET Longowal, Sangrur
Gurpreet Singh
Sant Longowal Institute of Engineering and Technology, Sangrur, Central University

Abstract

Hindi is the National language of India, which is still in its early stage of research and development regarding natural language processing applications in comparison to other languages like English, Chinese. Natural language processing is a field of Artificial Intelligence, which includes major tasks such as information retrieval, word segmentation, speech recognition, parsing, part of speech tagging, text classification, automatic text summarization etc. Spelling detection and correction in Hindi language is an important task of NLP which has not gotten sufficient attention till date. Spelling detection and correction for Indian languages such as Hindi is considered as a difficult task. Hindi Language is very different from English language in its phonetic properties and grammatical rules. Thus the existing techniques and methods that are being used to check the errors in English language can’t be used for Hindi Language. There are mainly two types of error: Non word error and real word error. Error detection for non-word error in Hindi language has been done but for real word error no work has been done till date. This paper focused on Real word spelling error detection and correction in Hindi text by using N Grams Model and Levensthein edit distance algorithm.

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Vol. 8 No. 7 (2017): July-August 2017
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Author Biographies

Shailza Kanwar, SLIET Longowal, Sangrur

M.Tech Scholar, CSE

Manoj Kumar Sachan, SLIET Longowal, Sangrur

Associate Professor, CSE

Gurpreet Singh, Sant Longowal Institute of Engineering and Technology, Sangrur, Central University

Research Scholar, CSE department

References

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