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New Wolof-Arabic parallel corpus released for machine translation research

Researchers have introduced MudawanSn, a new parallel corpus designed to improve machine translation between Wolof and Modern Standard Arabic. This resource consists of 1,271 sentence-aligned pairs derived from Senegalese news discourse, covering topics such as politics, society, religion, and sports. Benchmarking four machine translation systems, the study found that fine-tuning on MudawanSn significantly enhances translation quality, with the AfriNLLB-12 model achieving notable BLEU and chrF++ scores. The corpus is publicly available for use. AI

IMPACT Facilitates improved machine translation for the Wolof-Arabic language pair, potentially benefiting communication and access to information.

RANK_REASON The cluster describes the release of a new parallel corpus for machine translation research, including methodology and benchmarking results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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New Wolof-Arabic parallel corpus released for machine translation research

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The cluster describes the release of a new parallel corpus for machine translation research, including methodology and benchmarking results. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mouhamed Mbaye, Thierno Diop ·

    MudawanSn: A Gold-Standard Wolof-Arabic Parallel Corpus for Machine Translation

    arXiv:2609.17539v1 Announce Type: new Abstract: We present MudawanSn, a gold-standard resource of 1,271 sentence-aligned pairs manually translated from Wolof into Modern Standard Arabic (MSA). The source texts are drawn from the MasakhaNER corpus and cover politics, society, reli…