Autores
Tonja Atnafu Lambebo
Kolesnikova Olga
Gelbukh Alexander
Título EthioMT: Parallel Corpus for Low-resource Ethiopian Languages
Tipo Congreso
Sub-tipo Memoria
Descripción 5th Workshop on Resources for African Indigenous Languages, RAIL 2024 at LREC-COLING 2024 - Workshop Proceedings
Resumen Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in high-resource languages. However, the performance of MT leaves much to be desired for low-resource languages. This is due to the smaller size of available parallel corpora in these languages, if such corpora are available at all. NLP in Ethiopian languages suffers from the same issues due to the unavailability of publicly accessible datasets for NLP tasks, including MT. To help the research community and foster research for Ethiopian languages, we introduce EthioMT – a new parallel corpus for 15 languages. We also create a new benchmark by collecting a dataset for better-researched languages in Ethiopia. We evaluate the newly collected corpus and the benchmark dataset for 23 Ethiopian languages using transformer and fine-tuning approaches. © 2024 ELRA Language Resource Association.
Observaciones
Lugar Turin
País Italia
No. de páginas 107-114
Vol. / Cap.
Inicio 2024-05-25
Fin
ISBN/ISSN 9782493814401