The African Stopwords project: curating stopwords for African languages
Emezue, Chris, Nigatu, Hellina, Thinwa, Cynthia, Zhou, Helper, Muhammad, Shamsuddeen, Louis, Lerato, Abdulmumin, Idris, Oyerinde, Samuel, Ajibade, Benjamin, Samuel, Olanrewaju, Joshua, Oviawe, Onwuegbuzia, Emeka, Emezue, Handel, Ige, Ifeoluwatayo A., Tonja, Atnafu Lambebo, Chukwuneke, Chiamaka, Dossou, Bonaventure F. P., Etori, Naome A., Emmanuel, Mbonu Chinedu, Yousuf, Oreen, Aina, Kaosarat, David, Davis
–arXiv.org Artificial Intelligence
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 African Stopwords project aims to study and curate stopwords for African languages. When analysing text data and building various NLP models, stopwords might not add much value to the meaning of the document (Singh, 2019) depending on the NLP task (like text classification).
arXiv.org Artificial Intelligence
Mar-21-2023