Alina Telnova
2026
Scalable Generation of Adult-Oriented Therapeutic Reading Texts for Russian Aphasia Rehabilitation
Anastasia Kolmogorova | Anastasia Margolina | Alina Telnova | Igor Ilchenko
Proceedings of the Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026
Anastasia Kolmogorova | Anastasia Margolina | Alina Telnova | Igor Ilchenko
Proceedings of the Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026
Texts are widely used in aphasia rehabilitation to support the recovery of comprehension and narrative planning. In routine practice, clinical impact depends strongly on patient motivation and on the availability of age-appropriate reading materials: adults are often offered child-oriented texts, which can be perceived as demeaning and may reduce engagement. We present a controllable generation pipeline for building a repository of Russian therapeutic reading texts for adult aphasia therapy. An anonymized repository with code and data is available at https://github.com/z00logist/aphasia-exercises-generation. The pipeline conditions each story on an explicit semantic triplet (12 topics-10 archetypes-11 objects) and enforces three clinically motivated complexity regimes (Basic/Intermediate/Advanced). Using batched prompting, we generate 1,296 unique stories. We evaluate the corpus with classical linguistic metrics and a LLM-as-a-judge protocol (18 binary criteria); on a stratified sample of 198 stories, overall rubric compliance is 80.0%. Surface metrics show a monotonic increase in lexical and syntactic complexity across regimes, and Basic texts closely match a small clinical anchor set of 10 therapist-authored texts. Judge-based analysis indicates near-perfect adherence to high-level narrative constraints but persistent limitations in fine-grained phonotactic control, motivating hybrid neuro-symbolic enforcement.