Work

CMUQ$@$QALB-2014: An SMT-based System for Automatic Arabic Error Correction

Year: 2014

Type: conference-paper

Abstract: In this paper, we describe the CMUQ system we submitted to The ANLP-QALB 2014 Shared Task on Automatic Text Correction for Arabic.Our system combines rule-based linguistic techniques with statistical language modeling techniques and machine translationbased methods.Our system outperforms the baseline and reaches an F-score of 65.42% on the test set of QALB corpus.This ranks us 3rd in the competition.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.3115/v1/w14-3618

Authors: Serena Jeblee, Houda Bouamor, Wajdi Zaghouani, Kemal Oflazer

Institutions: Carnegie Mellon University, Carnegie Mellon University Qatar

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2251816508

FWCI: 1.571

Cites: 22

Cited by: 17

Related to: 10