Extended Parallel Corpus for Amharic-English Machine Translation

Andargachew Mekonnen Gezmu, Andreas Nürnberger, Tesfaye Bayu Bati

Abstract
This paper describes the acquisition, preprocessing, segmentation, and alignment of an Amharic-English parallel corpus. It will be helpful for machine translation of a low-resource language, Amharic. We freely released the corpus for research purposes. Furthermore, we developed baseline statistical and neural machine translation systems; we trained statistical and neural machine translation models using the corpus. In the experiments, we also used a large monolingual corpus for the language model of statistical machine translation and back-translation of neural machine translation. In the automatic evaluation, neural machine translation models outperform statistical machine translation models by approximately six to seven Bilingual Evaluation Understudy (BLEU) points. Besides, among the neural machine translation models, the subword models outperform the word-based models by three to four BLEU points. Moreover, two other relevant automatic evaluation metrics, Translation Edit Rate on Character Level and Better Evaluation as Ranking, reflect corresponding differences among the trained models.
Anthology ID:
2022.lrec-1.716
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6644–6653
Language:
URL:
https://aclanthology.org/2022.lrec-1.716
DOI:
Bibkey:
Cite (ACL):
Andargachew Mekonnen Gezmu, Andreas Nürnberger, and Tesfaye Bayu Bati. 2022. Extended Parallel Corpus for Amharic-English Machine Translation. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6644–6653, Marseille, France. European Language Resources Association.
Cite (Informal):
Extended Parallel Corpus for Amharic-English Machine Translation (Gezmu et al., LREC 2022)
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PDF:
https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.716.pdf
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