Translating Between Morphologically Rich Languages: An Arabic-to-Turkish Machine Translation System
İlknur Durgar El-Kahlout, Emre Bektaş, Naime Şeyma Erdem, Hamza Kaya
Abstract
This paper introduces the work on building a machine translation system for Arabic-to-Turkish in the news domain. Our work includes collecting parallel datasets in several ways for a new and low-resourced language pair, building baseline systems with state-of-the-art architectures and developing language specific algorithms for better translation. Parallel datasets are mainly collected three different ways; i) translating Arabic texts into Turkish by professional translators, ii) exploiting the web for open-source Arabic-Turkish parallel texts, iii) using back-translation. We per-formed preliminary experiments for Arabic-to-Turkish machine translation with neural(Marian) machine translation tools with a novel morphologically motivated vocabulary reduction method.- Anthology ID:
- W19-4617
- Volume:
- Proceedings of the Fourth Arabic Natural Language Processing Workshop
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 158–166
- Language:
- URL:
- https://aclanthology.org/W19-4617
- DOI:
- 10.18653/v1/W19-4617
- Cite (ACL):
- İlknur Durgar El-Kahlout, Emre Bektaş, Naime Şeyma Erdem, and Hamza Kaya. 2019. Translating Between Morphologically Rich Languages: An Arabic-to-Turkish Machine Translation System. In Proceedings of the Fourth Arabic Natural Language Processing Workshop, pages 158–166, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Translating Between Morphologically Rich Languages: An Arabic-to-Turkish Machine Translation System (Durgar El-Kahlout et al., WANLP 2019)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/W19-4617.pdf
- Data
- OpenSubtitles