Igbo-English Machine Translation : An Evaluation Benchmark

Ezeani, Ignatius and Rayson, Paul and Onyenwe, Ikechukwu E. and Chinedu, Uchechukwu and Hepple, Mark (2020) Igbo-English Machine Translation : An Evaluation Benchmark. In: Eighth International Conference on Learning Representations, 2020-04-26 - 2020-04-30, Virtual.

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Although researchers and practitioners are pushing the boundaries and enhancing the capacities of NLP tools and methods, works on African languages are lagging. A lot of focus on well resourced languages such as English, Japanese, German, French, Russian, Mandarin Chinese etc. Over 97% of the world's 7000 languages, including African languages, are low resourced for NLP i.e. they have little or no data, tools, and techniques for NLP research. For instance, only 5 out of 2965, 0.19% authors of full text papers in the ACL Anthology extracted from the 5 major conferences in 2018 ACL, NAACL, EMNLP, COLING and CoNLL, are affiliated to African institutions. In this work, we discuss our effort toward building a standard machine translation benchmark dataset for Igbo, one of the 3 major Nigerian languages. Igbo is spoken by more than 50 million people globally with over 50% of the speakers are in southeastern Nigeria. Igbo is low resourced although there have been some efforts toward developing IgboNLP such as part of speech tagging and diacritic restoration

Item Type:
Contribution to Conference (Paper)
Journal or Publication Title:
Eighth International Conference on Learning Representations : ICLR 2020
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Deposited On:
15 Apr 2020 11:00
Last Modified:
13 Jun 2024 23:52