3 papers
cs.CL2022
Explaining Translationese: why are Neural Classifiers Better and what do they Learn?
Kwabena Amponsah-Kaakyire, Daria Pylypenko, Josef van Genabith +1
Recent work has shown that neural feature- and representation-learning, e.g. BERT, achieves superior performance over traditional manual feature engineering based approaches, with…
cs.CL2021
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification
Daria Pylypenko, Kwabena Amponsah-Kaakyire, Koel Dutta Chowdhury +2
Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural…
cs.CL2019
Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi
Jesujoba O. Alabi, Kwabena Amponsah-Kaakyire, David I. Adelani +1
The success of several architectures to learn semantic representations from unannotated text and the availability of these kind of texts in online multilingual resources such as Wi…