Expanding FLORES+ benchmark for more low-resource settings: Portuguese-Emakhuwa machine translation evaluation

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Ali, Felermino (Author) Other; Cardoso, Henrique Lopes (Author) FEUP; Sousa-Silva, Rui (Author) FLUP

Conference proceedings International

Title: Ninth Conference on Machine Translation: WMT 2024

Pages: 579-592

9th Conference on Machine Translation

Miami, 2024

Other information

DOI: 10.48550/arXiv.2408.11457

Abstract (EN): As part of the Open Language Data Initiative shared tasks, we have expanded the FLORES+ evaluation set to include Emakhuwa, a lowresource language widely spoken in Mozambique. We translated the dev and devtest sets from Portuguese into Emakhuwa, and we detail the translation process and quality assurance measures used. Our methodology involved various quality checks, including postediting and adequacy assessments. The resulting datasets consist of multiple reference sentences for each source. We present baseline results from training a Neural Machine Translation system and fine-tuning existing multilingual translation models. Our findings suggest that spelling inconsistencies remain a challenge in Emakhuwa. Additionally, the baseline models underperformed on this evaluation set, underscoring the necessity for further research to enhance machine translation quality for Emakhuwa. The data is publicly available at https://huggingface.co/ datasets/LIACC/Emakhuwa-FLORES

Language: English

Type (Professor's evaluation): Scientific