@inproceedings{jeong-etal-2026-dementiabank,
    title = "{D}ementia{B}ank-Emotion: A Multi-Rater Emotion Annotation Corpus for {A}lzheimer{'}s Disease Speech (Version 1.0)",
    author = "Jeong, Cheonkam  and
      Liao, Jessica  and
      Lu, Audrey  and
      Song, Yutong  and
      Rashidian, Christopher  and
      Krogh, Donna  and
      Krogh, Erik  and
      Rasouli, Mahkameh  and
      Lee, Jung-Ah  and
      Dutt, Nikil  and
      Gibbs, Lisa M  and
      Sultzer, David  and
      Rousseau, Julie  and
      Ludlow, Jocelyn  and
      Galvez, Margaret  and
      Nuth, Alexander  and
      Khay, Chet  and
      Brunswicker, Sabine  and
      Nyamathi, Adeline",
    editor = {Danilova, Vera  and
      Kurfal{\i}, Murathan  and
      S{\"o}derfeldt, Ylva  and
      Reed, Julia  and
      Burchell, Andrew},
    booktitle = "Proceedings of the 1st Workshop on Linguistic Analysis for Health ({H}ea{L}ing 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.healing-1.28/",
    pages = "314--337",
    ISBN = "979-8-89176-367-8",
    abstract = "We present DementiaBank-Emotion, the first multi-rater emotion annotation corpus for Alzheimer{'}s disease (AD) speech. Annotating 1,492 utterances from 108 speakers for Ekman{'}s six basic emotions and neutral, we find that AD patients express significantly more non-neutral emotions (16.9{\%}) than healthy controls (5.7{\%}; p {\ensuremath{<}} .001). Exploratory acoustic analysis suggests a possible dissociation: control speakers showed substantial F0 modulation for sadness (Delta = -3.45 semitones from baseline), whereas AD speakers showed minimal change (Delta = +0.11 semitones; interaction p = .023), though this finding is based on limited samples (sadness: n=5 control, n=15 AD) and requires replication. Within AD speech, loudness differentiates emotion categories, indicating partially preserved emotion-prosody mappings. We release the corpus, annotation guidelines, and calibration workshop materials to support research on emotion recognition in clinical populations."
}