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The African Stopwords project: curating stopwords for African languages

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arxiv 2304.12155 v1 pith:YIWXZV2N submitted 2023-03-21 cs.CL cs.LG

Chris Emezue , Hellina Nigatu , Cynthia Thinwa , Helper Zhou , Shamsuddeen Muhammad , Lerato Louis , Idris Abdulmumin , Samuel Oyerinde
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Benjamin Ajibade Olanrewaju Samuel Oviawe Joshua Emeka Onwuegbuzia Handel Emezue Ifeoluwatayo A. Ige Atnafu Lambebo Tonja Chiamaka Chukwuneke Bonaventure F.P. Dossou Naome A. Etori Mbonu Chinedu Emmanuel Oreen Yousuf Kaosarat Aina Davis David
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classification cs.CLcs.LG
keywords stopwordsafricanlanguagesprojectinformationaimsavailabilityavailable
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Stopwords are fundamental in Natural Language Processing (NLP) techniques for information retrieval. One of the common tasks in preprocessing of text data is the removal of stopwords. Currently, while high-resource languages like English benefit from the availability of several stopwords, low-resource languages, such as those found in the African continent, have none that are standardized and available for use in NLP packages. Stopwords in the context of African languages are understudied and can reveal information about the crossover between languages. The \textit{African Stopwords} project aims to study and curate stopwords for African languages. In this paper, we present our current progress on ten African languages as well as future plans for the project.

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  1. A Case Against Implicit Standards: Homophone Normalization in Machine Translation for Languages that use the Ge'ez Script

    cs.CL 2025-07 conditional novelty 6.0 of 10

    Homophone normalization in Amharic training data can harm cross-lingual machine translation to Tigrinya and Ge'ez, but applying the normalization only at scoring time recovers BLEU gains.

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