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:
- 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)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.mtsummit-research.6.pdf
- Data
- JW300, OPUS-MT