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Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge
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Dementia is associated with various cognitive impairments and typically manifests only after significant progression, making intervention at this stage often ineffective. To address this issue, the Prediction and Recognition of Cognitive Decline through Spontaneous Speech (PROCESS) Signal Processing Grand Challenge invites participants to focus on early-stage dementia detection. We provide a new spontaneous speech corpus for this challenge. This corpus includes answers from three prompts designed by neurologists to better capture the cognition of speakers. Our baseline models achieved an F1-score of 55.0% on the classification task and an RMSE of 2.98 on the regression task.
Forward citations
Cited by 2 Pith papers
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Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech
A cascaded two-stage classifier and a multimodal feature ensemble beat the PROCESS 2025 challenge baselines for dementia detection and MMSE score prediction from spontaneous speech.
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Predicting Cognitive Decline: A Multimodal AI Approach to Dementia Screening from Speech
A multimodal speech-analysis pipeline ranks mid-pack in the PROCESS dementia screening challenge, though its reported rank numbers are internally inconsistent.
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