Speech Recognition, Named Entity Disambiguation(NED), Anaphora Resolution and Question Answering(QA) are some of the major areas of research in Natural Language Processing(NLP). Speech recognition systems will convert the human voice into corresponding text. Named Entity Disambiguation will identify the entity types in the given text. Anaphora Resolution is the process of finding antecedents of an anaphor and it has become a challenging task in the Computational Linguistics and Natural Language Processing(NLP). Question answering will develop systems that automatically answers the questions in natural language. Question answering system and Named Entity Disambiguation are the important fields intended to enhance the performance of the Information Retrieval System. This work mainly focused on integrating the above three tasks in a single system. Moreover this system will perform these tasks by receiving human speech as input and then converting it into the corresponding text. After the text conversion, Entity Disambiguation is performed on it. Real time speech input are given as the input. Anaphora resolution is also integrated with the disambiguation phase. The Question Answering System completely depends on the efficiency of entity disambiguation. The Answers are retrieved by searching based on these disambiguated entities. Anaphora Resolution will provide greater support for those entities that are not correctly identified in the disambiguation phase. Also the problem that anaphors that couldn`t find proper antecedents can easily find the correct ones since their entity type is correctly identified. The Question Answering System will perform better if the entities are correctly identified and disambiguated.

Speech Recognition, Named Entity Disambiguation, Anaphora Resolution, Question Answering, Natural Language Processing(NLP), Computational Linguistics

[1] Mena B. Habib, Maurice van Keulen , “NEED4Tweet: A Twitterbot for Tweets Named Entity Extraction Disambiguation”, Proceedings of ACL-IJCNLP 2015 System Demonstrations, pp. 31- 36, 2015.
[2] Danica Damljanovic and Kalina Bontcheva “Named Entity Disambiguation using Linked Data”, In proceedings of the 9th Extended Semantic Web Conference ESWC2012, pp. 334-336, 2012.
[3] Lev Ratinov, Dan Roth, Doug Downey, Mike Anderson “Local and Global Algorithms for Disambiguation to Wikipedia”, In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Volume 1, pp. 1375-1384, 2011.
[4] Mark Dredze, Paul McNamee, Delip Rao, Adam Gerber, Tim Finin, “Entity Disambiguation for Knowledge Base Population”, COLING ’10 Proceedings of the 23rd International Conference on Computational Linguistics, pp. 277- 285, 2010.
[5] Vipin Kumar, Pandey Shreya, Solanki Kamini Sharma, “A Technique for Anaphora Resolution of Text”, In proceedings of the International Journal of Applied Information Systems IJAIS, volume 5, pp. 0868-2249, 2013.
[6] Eugene Charniak and Micha Elsner, “EM Works for Pronoun Anaphora Resolution”, In Proceedings of the 12th Conference of the European Chapter of the ACL EACL 2009, pp. 146-158, 2009.
[7] Kalyani P. Kamune, Avinash Agrawal, Hybrid Approach to Pronominal Anaphora Resolution in English Newspaper Text, International Journal of Intelligent Systems and Applications(IJISA), vol 7, pp. 56-64, 2015.
[8] Smita Singh, Priya Lakhmani, Dr. Pratistha Mathur, Dr.Sudha Morwal, Analysis of Anaphora Resolution System for English Language, In proceedings of International Journal on Information Theory (IJIT), vol 3, pp. 51-57, 2014.
[9] Niyu Ge, John Hale, Eugene Charniak, A Statistical Approach to Anaphora Resolution, In proceedings of the workshop on very large corpora, pp. 161-170, 1998.
[10] Gayatri Chavan, Sonal Gore, Design of the Effective Question Answering System by Performing Question Analysis using the Classifier,International Journal of Computer Applications Foundation of Computer Science (FCS), NY, USA, vol 139, pp. 1-3, 2016.
[11] Marcus Klang, Pierre Nugues, Named Entity Disambiguation in a Question Answering System, The Fifth Swedish Language Technology Conference (SLTC 2014), 2014.
[12] Rohini Srihari, Wei Li, A Question Answering System Supported by Information Extraction, In Proceedings of the sixth conference on Applied natural language processing, pp. 166-172, 2000.
[13] Taniya Mishra, Srinivas Bangalore, Qme! : A Speech based Question-Answering system on Mobile Devices, In Proceeding HLT ’10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 55-63, 2010.