The 1st workshop on Readability for Low Resourced Languages

16 May 2023

Lancaster University 🔹 Sheffield Hallam University 🔹 King Saud University


About the workshop

Join us for an exciting workshop where experts in the field of natural language processing will come together to discuss the latest research and innovative approaches to assessing the readability of low-resource languages. We will delve into the development of a comprehensive Readability Framework, utilizing cutting-edge machine learning techniques to pre-process and identify key factors that impact text readability. The ultimate goal of the workshop is to discuss best practices and state-of-the-art AI-based approaches to create mathematical representations of expected readability levels at different school grade or cognitive ability levels. The workshop will also focus on utilising classifiers that are intuitive for humans to understand and adjust, enabling the analysis and improvement of the decision-making criteria. The main objectives of the workshop are three folds: a) increase awareness of the importance of readability in low-resource languages and its impact on language learning and literacy, b) discuss the challenges of readability in low-resource languages, such as limited resources and lack of standardization, and brainstorm strategies for addressing these challenges, and c) foster a community of practice among participants, allowing them to share their experiences and best practices for addressing readability issues in low-resource languages.

Call for speakers:

We invite researchers and practitioners to submit abstract proposals for talks related to the development of a Readability Framework for low-resource languages. The abstracts proceedings will appear in the Computing Research Repository (CoRR). Topics of interest include, but are not limited to:

• Machine learning for text readability • Applications of readability assessment
• Readability in low-resource languages • Comprehensibility measures
• Mathematical representations of readability levels • Text simplification for low-resource languages
• Readability & comprehensibility in language learning • The effects of text simplification on readability
• Readability frameworks for indigenous languages • Updating readability representations