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A SMS normalization system integrating multiple grammatical resources

Published online by Cambridge University Press:  07 June 2012

J. OLIVA ,
J. I. SERRANO ,
M. D. DEL CASTILLO  and
Á. IGESIAS
J. OLIVA
Affiliation:
Bioengineering Group.Spanish National Research Council (CSIC)Ctra. de Campo Real, km 0,200. La Poveda, Arganda del Rey. CP: 28500, Madrid, Spain e-mails: jesus.oliva@csic.es, jignacio.serrano@csic.es, md.delcastillo@csic.es, angel.iglesias@csic.es
J. I. SERRANO
Affiliation:
Bioengineering Group.Spanish National Research Council (CSIC)Ctra. de Campo Real, km 0,200. La Poveda, Arganda del Rey. CP: 28500, Madrid, Spain e-mails: jesus.oliva@csic.es, jignacio.serrano@csic.es, md.delcastillo@csic.es, angel.iglesias@csic.es
M. D. DEL CASTILLO
Affiliation:
Bioengineering Group.Spanish National Research Council (CSIC)Ctra. de Campo Real, km 0,200. La Poveda, Arganda del Rey. CP: 28500, Madrid, Spain e-mails: jesus.oliva@csic.es, jignacio.serrano@csic.es, md.delcastillo@csic.es, angel.iglesias@csic.es
Á. IGESIAS
Affiliation:
Bioengineering Group.Spanish National Research Council (CSIC)Ctra. de Campo Real, km 0,200. La Poveda, Arganda del Rey. CP: 28500, Madrid, Spain e-mails: jesus.oliva@csic.es, jignacio.serrano@csic.es, md.delcastillo@csic.es, angel.iglesias@csic.es
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Abstract

SMS language presents special phenomena and important deviations from natural language. Every day, an impressive amount of chat messages, SMS messages, and e-mails are sent all over the world. This widespread use makes important the development of systems that normalize SMS language into natural language. However, typical machine translation approaches are difficult to adapt to SMS language because of many irregularities that are shown by this kind of language. This paper presents a new approach for SMS normalization that combines lexical and phonological translation techniques with disambiguation algorithms at two different levels: lexical and semantic. The method proposed does not depend on big annotated corpus, which is difficult to build and is applied in two different domains showing its easiness of adaptation across different languages and domains. The results obtained by the system outperform some of the existing methods of SMS normalization despite the fact that the Spanish language and the corpus created have some features that complicate the normalization task.

Type
Articles
Information
Natural Language Engineering , Volume 19 , Issue 1 , January 2013 , pp. 121 - 141
Copyright
Copyright © Cambridge University Press 2012

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