Proffiliadur: Welsh Language Text Profiling Toolkit

May 11, 2026·
Nicolás Gutiérrez-Rolón
,
Jonathan Davies
,
Tomos Williams
,
Dawn Knight
Fernando Alva-Manchego
Fernando Alva-Manchego
· 0 min read
Abstract
We introduce Proffiliadur, a Python toolkit for text profiling and readability analysis in Welsh. The toolkit computes 141 surface, lexical, morphological, and syntactic indices, designed to capture linguistic variation while incorporating a Welsh-specific tokenisation process that enables accurate morphological analysis and handles phenomena such as initial consonant mutation. Proffiliadur enables systematic assessment of text accessibility and supports applications in education, healthcare, and public communication. We demonstrate the toolkit’s usefulness through two complementary analyses. First, we examine texts written in accordance with the Cymraeg Clîr (“Clear Welsh”) principles and compare them with regular Welsh texts. Second, we analyse texts across CEFR proficiency levels to explore how linguistic complexity varies with learner ability. We also evaluate feature-based and neural classification models for automatic complexity detection, showing that interpretable linguistic indices alone achieve strong predictive performance (F1 = 0.94), comparable to a fine-tuned transformer (F1 = 0.97). Proffiliadur provides the first dedicated text profiling toolkit for Welsh, offering reproducible, linguistically grounded measures of readability for a low-resource language.
Type
Publication
LREC 2026
publication
Fernando Alva-Manchego
Authors
Researcher in Natural Language Processing
My research interests include text simplification, readability assessment, multilingual NLP, Welsh language technology, and NLP for education and social care.