ArticleSensors (Basel, Switzerland)2022
Dementia Detection from Speech Using Machine Learning and Deep Learning Architectures.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 86 citations in OpenAlex.
- Natural language processing for geriatric syndromes: a systematic review of methods, applications, and challenges.BMC medical informatics and decision making · 2026Pooled it
- Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review.Frontiers in neurology · 2024Pooled it
- Multidimensional Prosodic and Semantic Coherence Modeling for Mandarin Mild Cognitive Impairment Detection.Bioengineering (Basel, Switzerland) · 2026Article
- PROTOCOL: Barriers and Facilitators to the Adoption of Speech-Based Cognitive Screening Tools: A Protocol for Systematic Review of Qualitative Evidence.Campbell systematic reviews · 2026Review
- Towards a speech-based digital biomarker for cognitive impairment: speech as a proxy for cognitive assessment.NPJ digital medicine · 2026Article
- Integrating acoustic, prosodic, and phonological features for automatic Alzheimer's detection.Frontiers in aging neuroscience · 2026Article
- Query-based multimodal interaction and adaptive gated fusion for Alzheimer's disease detection.Frontiers in aging neuroscience · 2026Article
- Multimodal Siamese networks for dementia detection from speech in women.Scientific reports · 2025Article
- Alzheimer's disease recognition based on waveform and spectral speech signal processing.Biomedical engineering letters · 2025Article
- Stacking model framework reveals clinical biochemical data and dietary behavior features associated with type 2 diabetes: A retrospective cohort study.APL bioengineering · 2024Article
- Sound as a bell: a deep learning approach for health status classification through speech acoustic biomarkers.Chinese medicine · 2024Article
- Multimodal deep learning for dementia classification using text and audio.Scientific reports · 2024Article
- Addressing energy challenges in Iraq: Forecasting power supply and demand using artificial intelligence models.Heliyon · 2024Article
- Article
- Human-Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention.Sensors (Basel, Switzerland) · 2023Article
- A Proposed Framework for Early Prediction of Schistosomiasis.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
Dementia affects the patient's memory and leads to language impairment. Research has demonstrated that speech and language deterioration is often a clear indication of dementia and plays a crucial role in the recognition process. Even though earlier studies have used speech features to recognize subjects suffering from dementia, they are often used along with other linguistic features obtained from transcriptions. This study explores significant standalone speech features to recognize dementia. The primary contribution of this work is to identify a compact set of speech features that aid in the dementia recognition process. The secondary contribution is to leverage machine learning (ML) and deep learning (DL) models for the recognition task. Speech samples from the Pitt corpus in Dementia Bank are utilized for the present study. The critical speech feature set of prosodic, voice quality and cepstral features has been proposed for the task. The experimental results demonstrate the superiority of machine learning (87.6 percent) over deep learning (85 percent) models for recognizing Dementia using the compact speech feature combination, along with lower time and memory consumption. The results obtained using the proposed approach are promising compared with the existing works on dementia recognition using speech.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.