SMS Text Normalization Using Hybrid Approach

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-21 Number-3
Year of Publication : 2015
Authors : Sakshi Goyal, Er.charandeep Singh Bedi
  10.14445/22312803/IJCTT-V21P124

MLA

Sakshi Goyal , Er.charandeep Singh Bedi "SMS Text Normalization Using Hybrid Approach". International Journal of Computer Trends and Technology (IJCTT) V21(3):126-129, March 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Text normalization is a task of generating plain text from an un normalized text. Mobile technology has contributed to the evolution of several media of communication such as chats, emails and short message service (SMS) text. This has significantly influenced the traditional standard way of expressing views from letter writing to a high-tech form of expression known as texting language. In this paper we present a review on various techniques to used translate a un normalized text into its equivalent plain text.

References
[1]Stefan Krawczyk Karthik Raghunathan. Investigating sms text normalization using statistical machine translation.Stanford University,Stanford, CA.
[2]RichardBeaufort, Sophie Roekhaut, Louise-Amélie Cougnon, Cédrick Fairon. A hybrid rule/model-based finite-state framework for normalizing SMS messages.
[3]ChenLi Yang Liu,Improving Text Normalization Using Character-blocks based Models and SystemCombination.
[4]Noam Chomsky and Morris Halle. 1968. The sound pattern of English. Harper and Row, New York, NY.
[5]AiTi Aw, Min Zhang, Juan Xiao, Jian Su A Phrase-based Statistical Model for SMS Text Normalization Institute of Infocomm Research 21 Heng Mui Keng Terracegapore 119613.
[6]Ademola O. Adesina, Kehinde K. Agbele, Nureni A. Azeez, Ademola P. Abidoye , A Query-Based SMS Translation in Information Access System . [7]Automatic normalization of short texts by combining statistical and rulebased techniques.Architecture for Text Normalization using Statistical Machine Translation techniques.
[8]w, AiTi and Zhang, Min and Xiao, Juan and Su, Jian,”A phrase-based statistical model for SMS text normalization”, Proceedings of the COLING/ACL on Main conference poster sessions,2006, pages 33–40, Sydney, Australia.
[9]Catherine Kobus, François Yvon, and Géraldine Damnati. Normalizingsms: are two metaphors better than one? In COLING ’08: Proceedings of the 22nd International Conference on Computational Linguistics, pages 441–448, Morristown, NJ, USA, 2008. Association for Computational Linguistics.
[10]A Machine-Translation Method for Normalization of SMS Darnes Vilari˜no, David Pinto, Beatriz Beltr´an, Saul Le´on, Esteban Castillo, and Mireya Tovar
[11]Tim Schlepped, Chenfei Zhu, Jan Gebhardt, Tanja Schultz Text Normalization based on Statistical Machine Translation and Internet User Support Cognitive Systems Lab, Karlsruhe Institute of Technology (KIT), Germany.
[12]Congle Zhang Adaptive Parser-Centric Text Normalization Dept of Computer Science and Engineering University of Washington, Seattle, WA 98195, USA.
[13] Choudhury, Monojit, Rahul Saraf, Vijit Jain, Sudeshna Sarkar, and Anupam Basu. 2007. Investigation and modeling of the structure of texting language.

Keywords
Text Normalization, Statistical Machine Translation Approach, Nearest word locater, Dictionary lookup.