@article{klein-etal-2026-towards,
    title = "Towards Clinical Applications of {NLP}: Detecting Emotion Regulation via Emotional Categories and Expression Modes in {F}rench Transcriptions",
    author = "Klein, Salome  and
      Todirascu, Amalia  and
      Vassiliadou, H{\'e}l{\`e}ne",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.660/",
    pages = "8347--8364",
    abstract = "We present an annotated corpus of patient interview transcriptions, labeled for emotionality, polarity, intensity, and emotional category (at the sentence level), and for expression mode (at the token level). Three modes of expression are distinguished: Designated (explicit), Suggested (implicit causes), and Manifested (implicit consequences). The corpus has been collected during the GREMO-LING project and is used to measure the linguistic expressions of emotions in patients' narratives. The corpus, consisting of 7,471 sentences, was used to fine-tune and evaluate several transformer-based language models, including the French BERT family. Sentence classification was performed for emotionality, emotion categories and expression modes. The best-performing models achieved F1 scores of 0.87 (emotionality, fine-tuned DistilCamemBERT), 0.58 (emotion categories, CamemBERTaV2), and 0.70 (expression modes, CamemBERT). We obtain solid results despite the high complexity of non-standard, spoken-derived data. These findings confirm the feasibility and relevance of automatic emotion detection in clinical discourse. We provide publicly available guidelines, annotated corpora and models, thereby establishing a methodological foundation for future research on the linguistic assessment of emotional regulation and its clinical implications, such as the evaluation of the Dialectical Behavioral Theray (DBT) in enhancing patients' emotion regulation skills."
}