Expanding FLORES+ Benchmark for More Low-Resource Settings: Portuguese-Emakhuwa Machine Translation Evaluation

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

Authors

António Ali, FDM (Author) Other; Henrique Lopes Cardoso (Author) FEUP; Silva, RS (Author) Other

Conference proceedings International

Title: Ninth Conference on Machine Translation: WMT 2024

Pages: 579-592

9th Conference on Machine Translation

Miami, 2024

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-018-0DY

Abstract (EN): As part of the Open Language Data Initiative shared tasks, we have expanded the FLORES+ evaluation set to include Emakhuwa, a low-resource 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 post-editing 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 ©2024 Association for Computational Linguistics.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13