A Hybrid Rules and Statistical Method for Arabic to English Machine Translation

Arwa Alqudsi, Nazlia Omar, Khalid Shaker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Arabic is one of the six major world languages. It originated in the area currently known as the Arabian Peninsula. Arabic is the joint official language in Middle Eastern and African states. Large communities of Arabic speakers have existed outside of the Middle East since the end of the last century, particularly in the United States and Europe. So finding a quick and efficient Arabic machine translator has become an urgent necessity, due to the differences between the languages spoken in the world's communities and the vast development that has occurred worldwide. Arabic combines many of the significant challenges of other languages like word order and ambiguity. The word ordering problem because of Arabic has four sentence structures which allow different word orders. Ambiguity in the Arabic language is a notorious problem because of the richness and complexity of Arabic morphology. The core problems in machine translation are reordering the words and estimating the right word translation among many options in the lexicon. The Rule-Based Machine translation (RBMT) approach is the way to reorder words, and the statistical approach, such as Expectation Maximisation (EM), is the way to select right word translations and count word frequencies. Combining RBMT with EM plays an impotent role in generating a good-quality MT. This paper presents a combination of the rule-based machine translation (RBMT) approach with the Expectation Maximisation (EM) algorithm. These two techniques have been applied successfully to word ordering and ambiguity problems in Arabic-to-English machine translation.

Original languageEnglish
Title of host publication2nd International Conference on Computer Applications and Information Security, ICCAIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728101088
DOIs
Publication statusPublished - May 2019
Event2nd International Conference on Computer Applications and Information Security, ICCAIS 2019 - Riyadh, Saudi Arabia
Duration: 1 May 20193 May 2019

Publication series

Name2nd International Conference on Computer Applications and Information Security, ICCAIS 2019

Conference

Conference2nd International Conference on Computer Applications and Information Security, ICCAIS 2019
CountrySaudi Arabia
CityRiyadh
Period1/5/193/5/19

Fingerprint

Statistical methods
Language
Social Planning
Middle East
Joints
Machine translation
Rule-based

Keywords

  • Arabic machine translation problems
  • Expectation Maximisation
  • Hybrid Approach

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Health Informatics
  • Information Systems
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

Cite this

Alqudsi, A., Omar, N., & Shaker, K. (2019). A Hybrid Rules and Statistical Method for Arabic to English Machine Translation. In 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019 [8769545] (2nd International Conference on Computer Applications and Information Security, ICCAIS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAIS.2019.8769545

A Hybrid Rules and Statistical Method for Arabic to English Machine Translation. / Alqudsi, Arwa; Omar, Nazlia; Shaker, Khalid.

2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8769545 (2nd International Conference on Computer Applications and Information Security, ICCAIS 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alqudsi, A, Omar, N & Shaker, K 2019, A Hybrid Rules and Statistical Method for Arabic to English Machine Translation. in 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019., 8769545, 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019, Riyadh, Saudi Arabia, 1/5/19. https://doi.org/10.1109/CAIS.2019.8769545
Alqudsi A, Omar N, Shaker K. A Hybrid Rules and Statistical Method for Arabic to English Machine Translation. In 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8769545. (2nd International Conference on Computer Applications and Information Security, ICCAIS 2019). https://doi.org/10.1109/CAIS.2019.8769545
Alqudsi, Arwa ; Omar, Nazlia ; Shaker, Khalid. / A Hybrid Rules and Statistical Method for Arabic to English Machine Translation. 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2nd International Conference on Computer Applications and Information Security, ICCAIS 2019).
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