Search Results for author: Ignatius Ezeani

Found 15 papers, 6 papers with code

IgboBERT Models: Building and Training Transformer Models for the Igbo Language

1 code implementation LREC 2022 Chiamaka Chukwuneke, Ignatius Ezeani, Paul Rayson, Mahmoud El-Haj

Our results show that, although the IgboNER task benefited hugely from fine-tuning large transformer model, fine-tuning a transformer model built from scratch with comparatively little Igbo text data seems to yield quite decent results for the IgboNER task.

Language Modelling named-entity-recognition +2

Creation of an Evaluation Corpus and Baseline Evaluation Scores for Welsh Text Summarisation

no code implementations CLTW (LREC) 2022 Mahmoud El-Haj, Ignatius Ezeani, Jonathan Morris, Dawn Knight

As part of the effort to increase the availability of Welsh digital technology, this paper introduces the first human vs metrics Welsh summarisation evaluation results and dataset, which we provide freely for research purposes to help advance the work on Welsh summarisation.

Introducing the Welsh Text Summarisation Dataset and Baseline Systems

1 code implementation LREC 2022 Ignatius Ezeani, Mahmoud El-Haj, Jonathan Morris, Dawn Knight

Welsh is an official language in Wales and is spoken by an estimated 884, 300 people (29. 2% of the population of Wales).

Text Summarization

MasakhaNER: Named Entity Recognition for African Languages

2 code implementations22 Mar 2021 David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, Daniel D'souza, Julia Kreutzer, Constantine Lignos, Chester Palen-Michel, Happy Buzaaba, Shruti Rijhwani, Sebastian Ruder, Stephen Mayhew, Israel Abebe Azime, Shamsuddeen Muhammad, Chris Chinenye Emezue, Joyce Nakatumba-Nabende, Perez Ogayo, Anuoluwapo Aremu, Catherine Gitau, Derguene Mbaye, Jesujoba Alabi, Seid Muhie Yimam, Tajuddeen Gwadabe, Ignatius Ezeani, Rubungo Andre Niyongabo, Jonathan Mukiibi, Verrah Otiende, Iroro Orife, Davis David, Samba Ngom, Tosin Adewumi, Paul Rayson, Mofetoluwa Adeyemi, Gerald Muriuki, Emmanuel Anebi, Chiamaka Chukwuneke, Nkiruka Odu, Eric Peter Wairagala, Samuel Oyerinde, Clemencia Siro, Tobius Saul Bateesa, Temilola Oloyede, Yvonne Wambui, Victor Akinode, Deborah Nabagereka, Maurice Katusiime, Ayodele Awokoya, Mouhamadane MBOUP, Dibora Gebreyohannes, Henok Tilaye, Kelechi Nwaike, Degaga Wolde, Abdoulaye Faye, Blessing Sibanda, Orevaoghene Ahia, Bonaventure F. P. Dossou, Kelechi Ogueji, Thierno Ibrahima DIOP, Abdoulaye Diallo, Adewale Akinfaderin, Tendai Marengereke, Salomey Osei

We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.

named-entity-recognition Named Entity Recognition +2

Infrastructure for Semantic Annotation in the Genomics Domain

no code implementations LREC 2020 Mahmoud El-Haj, Nathan Rutherford, Matthew Coole, Ignatius Ezeani, Sheryl Prentice, Nancy Ide, Jo Knight, Scott Piao, John Mariani, Paul Rayson, Keith Suderman

The corpus database is distributed to permit fast indexing, and provides a simple web front-end with corpus linguistics methods for sub-corpus comparison and retrieval.


Igbo-English Machine Translation: An Evaluation Benchmark

no code implementations1 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.

Machine Translation Part-Of-Speech Tagging +1

Leveraging Pre-Trained Embeddings for Welsh Taggers

no code implementations WS 2019 Ignatius Ezeani, Scott Piao, Steven Neale, Paul Rayson, Dawn Knight

While the application of word embedding models to downstream Natural Language Processing (NLP) tasks has been shown to be successful, the benefits for low-resource languages is somewhat limited due to lack of adequate data for training the models.

Igbo Diacritic Restoration using Embedding Models

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.

Machine Translation Word Embeddings

Lexical Disambiguation of Igbo using Diacritic Restoration

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.

BIG-bench Machine Learning General Classification

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