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New dataset MGhana-ST targets low-resource Ghanaian languages

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MGhana-ST, a new speech translation dataset designed for four low-resource Ghanaian languages: Ga, Twi, Ewe, and Fante. The dataset, which includes paired audio and English translations with annotations for verbal and non-verbal events, is intended to advance research in African language speech technology. Experiments using the Whisper-small model revealed that flat multilingual training under data scarcity did not benefit all languages, with some showing declines in performance compared to monolingual training. AI

IMPACT This dataset and its analysis could inform future research and development of speech technology for underrepresented languages.

RANK_REASON The cluster describes a new academic paper introducing a dataset and experimental results on multilingual training trade-offs for low-resource languages. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset MGhana-ST targets low-resource Ghanaian languages

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The cluster describes a new academic paper introducing a dataset and experimental results on multilingual training trade-offs for low-resource languages. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Frank Lawrence Nii Adoquaye Acquaye, Eric George Parakal, Jesse Johnson, Kishankumar Bhimani, Jochebed Afua Basil ·

    MGhana-ST: A Low-Resource Speech Translation Dataset for Ghanaian Languages and an Analysis of Multilingual Training Trade-offs

    arXiv:2609.40041v1 Announce Type: new Abstract: We present MGhana-ST, a speech translation dataset for four low-resource Ghanaian language varieties: Ga, Twi (Akuapem and Asante), Ewe, and Fante. MGhana-ST is an ongoing annotation effort; the experiments here use a fixed subset o…

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