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The Impact of Pause and Filler Word Encoding on Dementia Detection with Contrastive Learning

https://doi.org/10.3390/app14198879

Soleimani, Reza; Guo, Shengjie; Haley, Katarina L; Jacks, Adam; Lobaton, Edgar (October 2024, Applied Sciences)

Dementia is primarily caused by neurodegenerative diseases like Alzheimer’s disease (AD). It affects millions worldwide, making detection and monitoring crucial. This study focuses on the detection of dementia from speech transcripts of controls and dementia groups. We propose encoding in-text pauses and filler words (e.g., “uh” and “um”) in text-based language models and thoroughly evaluating their impact on performance (e.g., accuracy). Additionally, we suggest using contrastive learning to improve performance in a multi-task framework. Our results demonstrate the effectiveness of our approaches in enhancing the model’s performance, achieving 87% accuracy and an 86% f1-score. Compared to the state of the art, our approach has similar performance despite having significantly fewer parameters. This highlights the importance of pause and filler word encoding on the detection of dementia.
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Alzheimer’s Disease Classification From Speech Pause Distributions With Context Information

https://doi.org/10.1109/EMBC53108.2024.10782834

Khatri, Geet; Soleimani, Reza; Haley, Katarina L; Jacks, Adam; Lobaton, Edgar (July 2024, IEEE)

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Dementia Detection by In-Text Pause Encoding

https://doi.org/10.1109/EMBC53108.2024.10781756

Soleimani, Reza; Guo, Shengjie; Haley, Katarina L; Jacks, Adam; Lobaton, Edgar (July 2024, IEEE)

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A Wearable System for Continuous Monitoring and Assessment of Speech, Gait, and Cognitive Decline for Early Diagnosis of ADRD

https://doi.org/10.1109/EMBC40787.2023.10339986

Dieffenderfer, James; Brewer, Alec; Noonan, Maxwell A.; Smith, Madeline; Eichenlaub, Emily; Haley, Katarina L.; Jacks, Adam; Lobaton, Edgar; Neupert, Shevaun D.; Hess, Thomas M.; et al (July 2023, Annual International Conference of the IEEE Engineering in Medicine and Biology Society)

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