A combined method based on stochastic and linguistic paradigm for the understanding of arabic spontaneous utterances

Authors:
Chahira Lhioui;Anis Zouaghi;Mounir Zrigui
Affiliations:
ISIM of Medenine, Gabes University, Medenine, Tunisia,LATICE Laboratory, ESSTT Tunis, Tunisia;ISSAT of Sousse, Sousse University, Taffala city (Ibn Khaldoun), Sousse, Tunisia;FSM of Monastir, Monastir University, Monastir, Tunisia
Venue:
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Year:
2013

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Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging

Computational Linguistics

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Abstract

ASTI is an Arabic-speaking spoken language understanding (SLU) system which carries out two kinds of analysis which are relatively opposed. It is designed for touristic field to tell trippers about something that interests them. Based on a dual approach, the system adapts the idea of stochastic approach to the probabilistic context free grammar (PCFG) (approach based on rules). This paper provides a detailed description of ASTI system as well as well as results compared with several international ones. The observed error rates suggest that our combined approach can stand a comparison with concept spotters on larger application domains.