The Serendipity of Claude AI: Case of the 13 Low-Resource National Languages of Mali
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866929742791311360 |
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| author | Dembele, Alou Coulibaly, Nouhoum Souleymane Leventhal, Michael |
| author_facet | Dembele, Alou Coulibaly, Nouhoum Souleymane Leventhal, Michael |
| contents | Recent advances in artificial intelligence (AI) and natural language processing (NLP) have improved the representation of underrepresented languages. However, most languages, including Mali's 13 official national languages, continue to be poorly supported or unsupported by automatic translation and generative AI. This situation appears to have slightly improved with certain recent LLM releases. The study evaluated Claude AI's translation performance on each of the 13 national languages of Mali. In addition to ChrF2 and BLEU scores, human evaluators assessed translation accuracy, contextual consistency, robustness to dialect variations, management of linguistic bias, adaptation to a limited corpus, and ease of understanding. The study found that Claude AI performs robustly for languages with very modest language resources and, while unable to produce understandable and coherent texts for Malian languages with minimal resources, still manages to produce results which demonstrate the ability to mimic some elements of the language. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_03380 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Serendipity of Claude AI: Case of the 13 Low-Resource National Languages of Mali Dembele, Alou Coulibaly, Nouhoum Souleymane Leventhal, Michael Computation and Language Recent advances in artificial intelligence (AI) and natural language processing (NLP) have improved the representation of underrepresented languages. However, most languages, including Mali's 13 official national languages, continue to be poorly supported or unsupported by automatic translation and generative AI. This situation appears to have slightly improved with certain recent LLM releases. The study evaluated Claude AI's translation performance on each of the 13 national languages of Mali. In addition to ChrF2 and BLEU scores, human evaluators assessed translation accuracy, contextual consistency, robustness to dialect variations, management of linguistic bias, adaptation to a limited corpus, and ease of understanding. The study found that Claude AI performs robustly for languages with very modest language resources and, while unable to produce understandable and coherent texts for Malian languages with minimal resources, still manages to produce results which demonstrate the ability to mimic some elements of the language. |
| title | The Serendipity of Claude AI: Case of the 13 Low-Resource National Languages of Mali |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2503.03380 |