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Using Sentence Simplification to Generate Paraphrase for Low Resource Punjabi Language
The field of natural language processing is growing in computer science, and generating paraphrases is a difficult task, especially for languages like Hindi, Punjabi, and Urdu, which are morphologically rich and have limited resources. This research article focuses on generating paraphrases for Punjabi, a morphologically rich Indian language, using a sentence simplification approach. The author employed several sentence simplification algorithms to simplify long Punjabi sentences and used antonym-synonym replacement to generate the paraphrases. The sentence simplification component of the system achieved a precision of 100%, recall of 95%, and an f-measure of 97.43% when tested with a set of data. The developed system's performance was analyzed using various complexity measurement parameters, and it was observed that a combination of lexical and syntactic simplifications yielded the best results.
Keywords
NLP, Punjabi Language Processing, Paraphrasing, Syntactic Simplification, Lexical Simplification.
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