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The Igbo-English Machine Translation Project

Project: Research

Description

With natural language processing (NLP), researchers aim to get the computer to identify and understand the patterns in human languages. This is often difficult because a language embeds many dynamic and varied properties in its syntaxes, pragmatics and phonology, which needs to be captured and processed. Over 95% of the world’s 7000 languages are low-resourced for NLP i.e. they have little or no data, tools, and techniques for NLP work.
This project contributes to the efforts in bridging the digital divide between the well-resourced (and researched) languages and the rest by building the translation benchmark dataset and baseline model for the Igbo language.

Layman's description

Building an evaluation benchmark and a baseline model for Igbo-English translation

Key findings

Work is on-going.
AcronymAfriLowResNLP
StatusActive
Effective start/end date3/02/2029/01/21
  • Ezeani, Ignatius (Principal Investigator)
  • Rayson, Paul (Principal Investigator)
  • Onyenwe, Ikechukwu E. (Principal Investigator)
  • Chinedu, Uchechukwu (Principal Investigator)