no code implementations • 1 Apr 2020 • Ignatius Ezeani, Paul Rayson, Ikechukwu Onyenwe, Chinedu Uchechukwu, Mark Hepple
Although researchers and practitioners are pushing the boundaries and enhancing the capacities of NLP tools and methods, works on African languages are lagging.
no code implementations • COLING 2018 • Ignatius Ezeani, Ikechukwu Onyenwe, Mark Hepple
Most minority languages face the challenge of lack of resources - data and technologies - for NLP research.
no code implementations • NAACL 2018 • Ignatius Ezeani, Mark Hepple, Ikechukwu Onyenwe, Enemouh Chioma
In this work, we applied embedding models to the diacritic restoration task and compared their performances to those of n-gram models.
no code implementations • WS 2017 • Ignatius Ezeani, Mark Hepple, Ikechukwu Onyenwe
However, as a classification task, diacritic restoration is well suited for and will be more generalisable with machine learning.
no code implementations • LREC 2016 • Emma Barker, Monica Paramita, Adam Funk, Emina Kurtic, Ahmet Aker, Jonathan Foster, Mark Hepple, Robert Gaizauskas
Second, we define a task-based evaluation framework for reader comment summarization that allows summarization systems to be assessed in terms of how well they support users in a time-limited task of identifying issues and characterising opinion on issues in comments.
no code implementations • LREC 2016 • Daniel Preo{\c{t}}iuc-Pietro, P. K. Srijith, Mark Hepple, Trevor Cohn
Streaming media provides a number of unique challenges for computational linguistics.