[PDF][PDF] Disfluencies and Fine-Tuning Pre-Trained Language Models for Detection of Alzheimer's Disease.
Disfluencies and language problems in Alzheimer's Disease can be naturally modeled by
fine-tuning Transformer-based pre-trained language models such as BERT and ERNIE …
fine-tuning Transformer-based pre-trained language models such as BERT and ERNIE …
Comparing pre-trained and feature-based models for prediction of Alzheimer's disease based on speech
Introduction: Research related to the automatic detection of Alzheimer's disease (AD) is
important, given the high prevalence of AD and the high cost of traditional diagnostic …
important, given the high prevalence of AD and the high cost of traditional diagnostic …
Learning language and acoustic models for identifying Alzheimer's dementia from speech
Alzheimer's dementia (AD) is a chronic neurodegenerative illness that manifests in a
gradual decline of cognitive function. Early identification of AD is essential for managing the …
gradual decline of cognitive function. Early identification of AD is essential for managing the …
To BERT or not to BERT: comparing speech and language-based approaches for Alzheimer's disease detection
Research related to automatically detecting Alzheimer's disease (AD) is important, given the
high prevalence of AD and the high cost of traditional methods. Since AD significantly affects …
high prevalence of AD and the high cost of traditional methods. Since AD significantly affects …
[PDF][PDF] Automatic Detection and Assessment of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios.
In this study, we analyze the use of speech and speaker recognition technologies and
natural language processing to detect Alzheimer disease (AD) and estimate mini-mental …
natural language processing to detect Alzheimer disease (AD) and estimate mini-mental …
[PDF][PDF] Multiscale System for Alzheimer's Dementia Recognition Through Spontaneous Speech.
This paper describes the Verisk submission to The ADReSS Challenge [1]. We analyze the
text data at both the word level and phoneme level, which leads to our best-performing …
text data at both the word level and phoneme level, which leads to our best-performing …
Comparing natural language processing techniques for Alzheimer's dementia prediction in spontaneous speech
Alzheimer's Dementia (AD) is an incurable, debilitating, and progressive neurodegenerative
condition that affects cognitive function. Early diagnosis is important as therapeutics can …
condition that affects cognitive function. Early diagnosis is important as therapeutics can …
Deep learning-based speech analysis for Alzheimer's disease detection: a literature review
Background Alzheimer's disease has become one of the most common neurodegenerative
diseases worldwide, which seriously affects the health of the elderly. Early detection and …
diseases worldwide, which seriously affects the health of the elderly. Early detection and …
[PDF][PDF] Using the Outputs of Different Automatic Speech Recognition Paradigms for Acoustic-and BERT-Based Alzheimer's Dementia Detection Through Spontaneous …
Exploring acoustic and linguistic information embedded in spontaneous speech recordings
has proven to be efficient for automatic Alzheimer's dementia detection. Acoustic features …
has proven to be efficient for automatic Alzheimer's dementia detection. Acoustic features …
Multi-modal fusion with gating using audio, lexical and disfluency features for Alzheimer's dementia recognition from spontaneous speech
This paper is a submission to the Alzheimer's Dementia Recognition through Spontaneous
Speech (ADReSS) challenge, which aims to develop methods that can assist in the …
Speech (ADReSS) challenge, which aims to develop methods that can assist in the …