Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages

Abubakar Auwal Khalid; Salisu Musa Borodo; Amina Abubakar Imam

Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages

Abubakar Auwal Khalid, Salisu Musa Borodo, Amina Abubakar Imam

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Abstract

We present an improved method for automaticparallel sentence alignment in low- resourcelanguages. We used CoHere multilingualembeddings and inverted softmax retrieval.Our technique achieved a higher F1-score of78.30% on the MAFAND-MT test set, comparedto the existing technique’s 54.75%. Precisionand recall have shown similar performance.We assessed the quality of the extracted data bydemonstrating that it outperforms the existingtechnique in terms of low-resource translationperformance.

Anthology ID:: 2026.africanlp-main.4
Volume:: Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026)
Month:: March
Year:: 2026
Address:: Rabat, Morocco
Editors:: Everlyn Asiko Chimoto, Constantine Lignos, Shamsuddeen Muhammad, Idris Abdulmumin, Clemencia Siro, David Ifeoluwa Adelani
Venues:: AfricaNLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 37–43
Language:
URL:: https://aclanthology.org/2026.africanlp-main.4/
DOI:
Bibkey:
Cite (ACL):: Abubakar Auwal Khalid, Salisu Musa Borodo, and Amina Abubakar Imam. 2026. Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages. In Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026), pages 37–43, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):: Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages (Khalid et al., AfricaNLP 2026)
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PDF:: https://aclanthology.org/2026.africanlp-main.4.pdf

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@inproceedings{khalid-etal-2026-leveraging,
    title = "Leveraging {C}o{H}ere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages",
    author = "Khalid, Abubakar Auwal  and
      Borodo, Salisu Musa  and
      Imam, Amina Abubakar",
    editor = "Chimoto, Everlyn Asiko  and
      Lignos, Constantine  and
      Muhammad, Shamsuddeen  and
      Abdulmumin, Idris  and
      Siro, Clemencia  and
      Adelani, David Ifeoluwa",
    booktitle = "Proceedings of the 7th Workshop on {A}frican Natural Language Processing ({A}frica{NLP} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.africanlp-main.4/",
    pages = "37--43",
    ISBN = "979-8-89176-364-7",
    abstract = "We present an improved method for automaticparallel sentence alignment in low- resourcelanguages. We used CoHere multilingualembeddings and inverted softmax retrieval.Our technique achieved a higher F1-score of78.30{\%} on the MAFAND-MT test set, comparedto the existing technique{'}s 54.75{\%}. Precisionand recall have shown similar performance.We assessed the quality of the extracted data bydemonstrating that it outperforms the existingtechnique in terms of low-resource translationperformance."
}

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%0 Conference Proceedings
%T Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages
%A Khalid, Abubakar Auwal
%A Borodo, Salisu Musa
%A Imam, Amina Abubakar
%Y Chimoto, Everlyn Asiko
%Y Lignos, Constantine
%Y Muhammad, Shamsuddeen
%Y Abdulmumin, Idris
%Y Siro, Clemencia
%Y Adelani, David Ifeoluwa
%S Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-364-7
%F khalid-etal-2026-leveraging
%X We present an improved method for automaticparallel sentence alignment in low- resourcelanguages. We used CoHere multilingualembeddings and inverted softmax retrieval.Our technique achieved a higher F1-score of78.30% on the MAFAND-MT test set, comparedto the existing technique’s 54.75%. Precisionand recall have shown similar performance.We assessed the quality of the extracted data bydemonstrating that it outperforms the existingtechnique in terms of low-resource translationperformance.
%U https://aclanthology.org/2026.africanlp-main.4/
%P 37-43

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Markdown (Informal)

[Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages](https://aclanthology.org/2026.africanlp-main.4/) (Khalid et al., AfricaNLP 2026)

Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages (Khalid et al., AfricaNLP 2026)

ACL

Abubakar Auwal Khalid, Salisu Musa Borodo, and Amina Abubakar Imam. 2026. Leveraging CoHere Multilingual Embeddings and Inverted Softmax Retrieval for Automatic Parallel Sentence Alignment in Low-Resource Languages. In Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026), pages 37–43, Rabat, Morocco. Association for Computational Linguistics.