Multilingual Modelling for Resource-Poor Languages

Project Details

Description

This Carlsberg Foundation - Semper Ardens:Accelerate Career grant deals with the inequalities in modern-day language technologies. The project employs 3 PhD students and a 3-year postdoc.

Language is the key to accessing the modern technology on which our society relies, such as online search, spelling correction, and automatic translation. However, out of the over 7,000 languages in the world, only a handful have access to such technology. This is in part due to state-of-the-art solutions requiring vast amounts of data, which is unavailable to most languages, which can be referred to as resource-poor. Hence, most languages are marginalized in the current technological development, and will continue to be so unless fundamental changes are made. My project is about addressing this issue, by making use of the fact that languages often have systematic similarities with one another, aiming to increase technological access to billions of speakers of resource-poor languages.

Due to the project's interdisciplinary angle, and its focus on human language, it is uniquely positioned to have a substantial social impact. An example of its importance can be found in the UN's Sustainable Development Goals, which outlines a concrete aim in this direction (9.c.), looking to increase ICT access in least developed countries. However, simply providing ICT access will not have the impact imagined for speakers of resource-poor languages, as physical access to ICT does not equate to access to modern technologies. Real access requires fundamental changes in how we approach these languages. When successful, the findings of the project has the potential to impact the lives of billions of speakers of low-resource languages in third-world regions, but also domestically in terms of, e.g., Faroese. In short, providing people with access to language technologies in their native languages, will lead to increased life quality and equality across both languages and cultures in the world.
StatusActive
Effective start/end date01/09/202231/08/2025

Funding

  • Google: DKK425,000.00
  • Carlsbergfondet: DKK5,000,000.00

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 10 - Reduced Inequalities

Keywords

  • Natural Language Processing
  • Computational Linguistics
  • Machine Learning
  • Artificial Intelligence
  • Language Models
  • Linguistics
  • Typology
  • NLP
  • Language

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