The Effect of Domain and Diacritics in Yoruba–English Neural Machine Translation

David Adelani, Dana Ruiter, Jesujoba Alabi, Damilola Adebonojo, Adesina Ayeni, Mofe Adeyemi, Ayodele Esther Awokoya, Cristina España-Bonet


Abstract
Massively multilingual machine translation (MT) has shown impressive capabilities and including zero and few-shot translation between low-resource language pairs. However and these models are often evaluated on high-resource languages with the assumption that they generalize to low-resource ones. The difficulty of evaluating MT models on low-resource pairs is often due to lack of standardized evaluation datasets. In this paper and we present MENYO-20k and the first multi-domain parallel corpus with a especially curated orthography for Yoruba–English with standardized train-test splits for benchmarking. We provide several neural MT benchmarks and compare them to the performance of popular pre-trained (massively multilingual) MT models both for the heterogeneous test set and its subdomains. Since these pre-trained models use huge amounts of data with uncertain quality and we also analyze the effect of diacritics and a major characteristic of Yoruba and in the training data. We investigate how and when this training condition affects the final quality of a translation and its understandability.Our models outperform massively multilingual models such as Google (+8.7 BLEU) and Facebook M2M (+9.1) when translating to Yoruba and setting a high quality benchmark for future research.
Anthology ID:
2021.mtsummit-research.6
Volume:
Proceedings of Machine Translation Summit XVIII: Research Track
Month:
August
Year:
2021
Address:
Virtual
Editors:
Kevin Duh, Francisco Guzmán
Venue:
MTSummit
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
61–75
Language:
URL:
https://aclanthology.org/2021.mtsummit-research.6
DOI:
Bibkey:
Cite (ACL):
David Adelani, Dana Ruiter, Jesujoba Alabi, Damilola Adebonojo, Adesina Ayeni, Mofe Adeyemi, Ayodele Esther Awokoya, and Cristina España-Bonet. 2021. The Effect of Domain and Diacritics in Yoruba–English Neural Machine Translation. In Proceedings of Machine Translation Summit XVIII: Research Track, pages 61–75, Virtual. Association for Machine Translation in the Americas.
Cite (Informal):
The Effect of Domain and Diacritics in Yoruba–English Neural Machine Translation (Adelani et al., MTSummit 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.mtsummit-research.6.pdf
Data
JW300OPUS-MT