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.
The African Stopwords project: curating stopwords for African languages
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abstract
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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cs.CL 1years
2025 1verdicts
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A Case Against Implicit Standards: Homophone Normalization in Machine Translation for Languages that use the Ge'ez Script
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.