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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.04247 |
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| _version_ | 1866910011141128192 |
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| author | Jeong, Cheonkam Liao, Jessica Lu, Audrey Song, Yutong Rashidian, Christopher Krogh, Donna Krogh, Erik Rasouli, Mahkameh Lee, Jung-Ah Dutt, Nikil Gibbs, Lisa M Sultzer, David Rousseau, Julie Ludlow, Jocelyn Galvez, Margaret Nuth, Alexander Khay, Chet Brunswicker, Sabine Nyamathi, Adeline |
| author_facet | Jeong, Cheonkam Liao, Jessica Lu, Audrey Song, Yutong Rashidian, Christopher Krogh, Donna Krogh, Erik Rasouli, Mahkameh Lee, Jung-Ah Dutt, Nikil Gibbs, Lisa M Sultzer, David Rousseau, Julie Ludlow, Jocelyn Galvez, Margaret Nuth, Alexander Khay, Chet Brunswicker, Sabine Nyamathi, Adeline |
| contents | 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 < .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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_04247 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | DementiaBank-Emotion: A Multi-Rater Emotion Annotation Corpus for Alzheimer's Disease Speech (Version 1.0) Jeong, Cheonkam Liao, Jessica Lu, Audrey Song, Yutong Rashidian, Christopher Krogh, Donna Krogh, Erik Rasouli, Mahkameh Lee, Jung-Ah Dutt, Nikil Gibbs, Lisa M Sultzer, David Rousseau, Julie Ludlow, Jocelyn Galvez, Margaret Nuth, Alexander Khay, Chet Brunswicker, Sabine Nyamathi, Adeline Computation and Language Sound 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 < .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. |
| title | DementiaBank-Emotion: A Multi-Rater Emotion Annotation Corpus for Alzheimer's Disease Speech (Version 1.0) |
| topic | Computation and Language Sound |
| url | https://arxiv.org/abs/2602.04247 |