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Mittal, Misha
- Clause Identification in English and Indian Languages: A Survey
Abstract Views :125 |
PDF Views:2
Authors
Misha Mittal
1,
Abhilasha
1
Affiliations
1 GZS Punjab Technical University, Bathinda, IN
1 GZS Punjab Technical University, Bathinda, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 13 (2014), Pagination: 179-184Abstract
The problem of identification of clauses in natural language processing is to find away to identify the each type of clause, e.g., Dependent clause, independent clause. Clause identification plays very important role in preprocessing task for language processing activities. This paper reports about the Clause Identification proposed for various Languages like English, Malayalam, Bengali and Urdu. Various clause identification approaches like Hidden Markov Model (HMM), Support Vector Model (SVM), and Rule based approaches, Maximum Entropy (ME) and Conditional Random Field (CRF), Entropy Guided Transformation Learning (ETL), have been used for POS tagging.Full Text
- An Automated Error Detection System for Indian Language Using Statistical Approach
Abstract Views :126 |
PDF Views:0
Authors
Affiliations
1 Assistant Professor, Department of Computer Science and Applications, Maharishi Markandeshvar Engineering college, Mullana, Ambala, IN
2 Research Scholar, Department of Computer Science and Applications, DAV University, Jalandhar, IN
3 Associate Professor, Department of Computer Science and Applications, DAV University, Jalandhar, IN
1 Assistant Professor, Department of Computer Science and Applications, Maharishi Markandeshvar Engineering college, Mullana, Ambala, IN
2 Research Scholar, Department of Computer Science and Applications, DAV University, Jalandhar, IN
3 Associate Professor, Department of Computer Science and Applications, DAV University, Jalandhar, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 35, No SP (2023), Pagination: 146-152Abstract
Grammatical error detection system also called grammar checker or syntactic analyzer is one of the advance tool for natural language processing. This tool plays an important role in proof reading and for development of many other natural language processing applications like machine translation, summarization, question answering system etc. In this research article, we proposed a framework for detection of grammatical error using statistical approach. Further in statistical approach, we used N-gram approach for detection of the grammatical errors. Corpus used for generation of n-grams is taken from Indian Languages Corpora Initiative. This corpus is annotated by using morphological analyzer followed by part of speech tagger. Bi-gram, tri-gram and quad gram of part of speech tags are generated by using the annotated corpus. On testing the proposed algorithm on self-generated test data for Punjabi language, Overall accuracy was 100 percent, recall was 87.2, and the f-measure was 93.16,according to us.Keywords
Error Detection System, NLP, N-Gram, Syntactic Analyzer, Morphological Analyzer, POS Tagger.Full Text
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