Raveesh Motlani


2016

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Shallow Parsing Pipeline - Hindi-English Code-Mixed Social Media Text
Arnav Sharma | Sakshi Gupta | Raveesh Motlani | Piyush Bansal | Manish Shrivastava | Radhika Mamidi | Dipti M. Sharma
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Developing language technology tools and resources for a resource-poor language: Sindhi
Raveesh Motlani
Proceedings of the NAACL Student Research Workshop

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A Finite-State Morphological Analyser for Sindhi
Raveesh Motlani | Francis Tyers | Dipti Sharma
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Morphological analysis is a fundamental task in natural-language processing, which is used in other NLP applications such as part-of-speech tagging, syntactic parsing, information retrieval, machine translation, etc. In this paper, we present our work on the development of free/open-source finite-state morphological analyser for Sindhi. We have used Apertium’s lttoolbox as our finite-state toolkit to implement the transducer. The system is developed using a paradigm-based approach, wherein a paradigm defines all the word forms and their morphological features for a given stem (lemma). We have evaluated our system on the Sindhi Wikipedia corpus and achieved a reasonable coverage of 81% and a precision of over 97%.