Abstract
In this paper we present a design and animplementation of a mobile assistant applicationthat understands and meets users' requests inTurkish language. The application is able tounderstand requests for a set of phone operationssuch as calling a contact or sending an email andrequests for a set of information services such asmap, weather, and traffic. The understanding ofuser queries relies on existing research onnatural language processing for Turkish and ahybrid approach of rule-based and statisticalclassification methods. Our performance testsrevealed high accuracy results for the operationsthat our application supports.
References
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- 0] G. Eryiğit, “ITU Turkish NLP web service,” in Proceedings of the Demonstrations at EACL 2014 (EACL). Gothenburg, Sweden: Association for Computational Linguistics, April 2014.
- 1] J.Nivre,J.Hall,J.Nilsson,A.Chanev,G.Eryiğit,S.Kübler,S.Ma rinov, and E. Marsi, “Maltparser: A language-independent system for data-driven dependency parsing,” Natural Language Engineering Journal, vol. 13, no. 2, pp. 99–135, 2007.
- 2] G. Eryiğit, J. Nivre, and K. Oflazer, “Dependency parsing of Turkish,” Computational Linguistics, vol. 34, no. 3, pp. 357–389, 2008.
- 3] D. Torunoğlu and G. Eryiğit, “A cascaded approach for social media text normalization of Turkish,” in 5th Workshop on Language Analysis for Social Media (LASM) at EACL. Gothenburg, Sweden: Association for Computational Linguistics, April 2014.
- 4] C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn., vol. 20, no. 3, pp. 273–297, Sep. 1995. [Online]. Available: http://dx.doi.org/10.1023/A:1022627411411
- 5] A. Monge and C. Elkan, “The field matching problem: Algorithms and applications,” in In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996, pp. 267–270
Abstract
References
- H. Sak, M. Saraclar, and T. Gungor, “Morphology-based and sub-word language modeling for turkish speech recognition,” in Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on. IEEE, 2010, pp. 5402–5405.
- J. Nivre, J. Hall, J. Nilsson, G. Eryig ́it, and S. Marinov, “Labeled pseudo-projective dependency parsing with support vector machines,” in Proceedings of the Tenth Conference on Computational Natural Language Learning. Association for Computational Linguistics, 2006, pp. 221– 225.
- S. Buchholz and E. Marsi, “Conll-x shared task on multilingual de- pendency parsing,” in Proceedings of the Tenth Conference on Compu- tational Natural Language Learning. Association for Computational Linguistics, 2006, pp. 149–164.
- K. Oflazer and Ì. Kuruöz, “Tagging and morphological disambiguation of turkish text,” in Proceedings of the fourth conference on Applied natural language processing. Association for Computational Linguistics, 1994, pp. 144– 149.
- G. A. Şeker and G. Eryiğit, “Initial explorations on using CRFs for Turkish named entity recognition,” in Proceedings of COLING 2012, Mumbai, India, 8-15 December 2012.
- M. Şahin, U. Sulubacak, and G. Eryiğit, “Redefinition of Turkish morphology using flag diacritics,” in Proceedings of The Tenth Symposium on Natural Language Processing (SNLP-2013), Phuket, Thailand, October 2013.
- J. C. Hawkins, W. B. Rees, D. O. Chyi, and R. Y. Haitani, Interface for processing of an alternate symbol in a computer device. Google Patents, dec ” 13” 2005, uS Patent 6,975,304.
- P. Sawhney, P. King, H. W. Ham, and L. Wang, Apparatus and method for mobile personal assistant. Google Patents, aug ” 11” 2011, uS Patent App. 13/207,781.
- A.NeusteinandJ.A.Markowitz,MobileSpeechandAdvanced Natural Language Solutions. Springer, 2013.
- 0] G. Eryiğit, “ITU Turkish NLP web service,” in Proceedings of the Demonstrations at EACL 2014 (EACL). Gothenburg, Sweden: Association for Computational Linguistics, April 2014.
- 1] J.Nivre,J.Hall,J.Nilsson,A.Chanev,G.Eryiğit,S.Kübler,S.Ma rinov, and E. Marsi, “Maltparser: A language-independent system for data-driven dependency parsing,” Natural Language Engineering Journal, vol. 13, no. 2, pp. 99–135, 2007.
- 2] G. Eryiğit, J. Nivre, and K. Oflazer, “Dependency parsing of Turkish,” Computational Linguistics, vol. 34, no. 3, pp. 357–389, 2008.
- 3] D. Torunoğlu and G. Eryiğit, “A cascaded approach for social media text normalization of Turkish,” in 5th Workshop on Language Analysis for Social Media (LASM) at EACL. Gothenburg, Sweden: Association for Computational Linguistics, April 2014.
- 4] C. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learn., vol. 20, no. 3, pp. 273–297, Sep. 1995. [Online]. Available: http://dx.doi.org/10.1023/A:1022627411411
- 5] A. Monge and C. Elkan, “The field matching problem: Algorithms and applications,” in In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996, pp. 267–270
Details
| Other ID | JA37MG86NE |
|---|---|
| Journal Section | Makaleler(Araştırma) |
| Authors | |
| Publication Date | November 2, 2014 |
| Published in Issue | Year 2014 Volume: 7 Issue: 1 |
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