TONY: an open-source TOolkit for Nlp in psYchology
Federico Ravenda, Sofia Irene Ravenda, Volodymyr Karpenko, Daniele Montagnani University of Pavia, Andrea Raballo, Antonietta Mira Università della Svizzera Italiana and Università dell'Insubria
原文摘要
The growing demand for Mental Health (MH) services highlights the need for scalable computational tools, yet progress in computational psychology is hindered by scarce sensitive data, complex assessment procedures, and high technical barriers. While language is a well-established marker of different MH conditions, existing NLP solutions are often fragmented, closed-source, or difficult to use, limiting their adoption in interdisciplinary research.We present TONY, an open-source, python TOolkit for NLP in clinical psYchology. TONY bridges traditional psycholinguistic analysis and modern NLP by combining interpretable lexical features with state-of-the-art lightweight transformer models within a unified and easy-to-use framework. This hybrid approach enables robust and transparent text analysis without relying on large-scale models or closed-source software.TONY is designed for researchers and practitioners working at the intersection of NLP and MH, facilitating collaboration across disciplines. Compared to the few existing systems, TONY offers a more comprehensive and exhaustive solution, reducing the barrier to entry through a unified, modular, and reproducible pipeline that integrates classical and neural approaches in a single open framework. The toolkit is released under an open-source license and is evaluated through multiple MH–related datasets, demonstrating its flexibility and effectiveness in low-resource settings
cs.CL
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) · 2026 · 正式发表