3 papers
cs.CL2026
Enhancing speech representation learning with cross-modal knowledge transfer with HGNN under low resource settings: the case study of Yemba
Yannick Yomie Nzeuhang, Paulin Melatagia Yonta, Marie Tahon
Acoustic representation learning is crucial for speech processing, yet low-resource languages (LRLs) face severe data scarcity, limiting the effectiveness of traditional and self-s…
cs.CL2026
Low resource cross-modal alignment using HGNN to enhance speech representation
Yannick Yomie Nzeuhang, Marie Tahon, Paulin Melatagia Yonta
Speech-text space alignment is a multimodal representation learning method consisting to map different speech and text into a shared representation space, leading to enrichment of…
cs.CL2020
Neurals Networks for Projecting Named Entities from English to Ewondo
Michael Franklin Mbouopda, Paulin Melatagia Yonta, Guy Stephane B. Fedim Lombo
Named entity recognition is an important task in natural language processing. It is very well studied for rich language, but still under explored for low-resource languages. The ma…