3 citations · 3 across the 6 of their papers we have counts for
7 papers
HausaNLP at SemEval-2025 Task 11: Hausa Text Emotion Detection
Sani Abdullahi Sani, Salim Abubakar, Falalu Ibrahim Lawan +2
This paper presents our approach to multi-label emotion detection in Hausa, a low-resource African language, for SemEval Track A. We fine-tuned AfriBERTa, a transformer-based model…
HausaNLP: Current Status, Challenges and Future Directions for Hausa Natural Language Processing
Shamsuddeen Hassan Muhammad, Ibrahim Said Ahmad, Idris Abdulmumin +9
Hausa Natural Language Processing (NLP) has gained increasing attention in recent years, yet remains understudied as a low-resource language despite having over 120 million first-l…
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45
People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…
Text Categorization Can Enhance Domain-Agnostic Stopword Extraction
Houcemeddine Turki, Naome A. Etori, Mohamed Ali Hadj Taieb +6
This paper investigates the role of text categorization in streamlining stopword extraction in natural language processing (NLP), specifically focusing on nine African languages al…
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo, Tajuddeen R. Gwadabe, Clara E. Rivera +49
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingu…
HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification
Saminu Mohammad Aliyu, Idris Abdulmumin, Shamsuddeen Hassan Muhammad +4
We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detection…