mlsanityData to 7 Oct 2026

Alzheimer's Disease Detection from Spontaneous Speech through Combining Linguistic Complexity and (Dis)Fluency Features with Pretrained Language Models

arXiv 2106.08689 ↗First posted 16 Jun 2021cs.CL cs.SD eess.AScited by 13

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Abstract (arXiv)

In this paper, we combined linguistic complexity and (dis)fluency features with pretrained language models for the task of Alzheimer's disease detection of the 2021 ADReSSo (Alzheimer's Dementia Recognition through Spontaneous Speech) challenge. An accuracy of 83.1% was achieved on the test set, which amounts to an improvement of 4.23% over the baseline model. Our best-performing model that integrated component models using a stacking ensemble technique performed equally well on cross-validation and test data, indicating that it is robust against overfitting.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 9 of its 34 references that are in the map. First posted on arXiv 16 Jun 2021.

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9 of 34 references.

References · 9

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
  3. 2019ERNIE 2.0: A Continual Pre-training Framework for Language Understandingcited by 230
  4. 2014A Convolutional Neural Network for Modelling Sentencescited by 163
  5. 2021Detecting cognitive decline using speech only: The ADReSSo Challengecited by 81
  6. 2020To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detectioncited by 49
  7. 2020Artificial Intelligence, speech and language processing approaches to monitoring Alzheimer's Disease: a systematic reviewcited by 29
  8. 2018Multi-Layer Ensembling Techniques for Multilingual Intent Classificationcited by 4
  9. 2015Dependency-based Convolutional Neural Networks for Sentence Embeddingcited by 3

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Citing papers per year: 2022: 4; 2023: 1; 2024: 4; 2025: 3; 2026: 1.

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  1. 2022Pushing on Personality Detection from Verbal Behavior: A Transformer Meets Text Contours of Psycholinguistic Featurescited by 10
  2. 2022Exploring linguistic feature and model combination for speech recognition based automatic AD detectioncited by 9
  3. 2025LLMCARE: early detection of cognitive impairment via transformer models enhanced by LLM-generated synthetic datacited by 8
  4. 2022Exploiting prompt learning with pre-trained language models for Alzheimer's Disease detectioncited by 6
  5. 2023Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speechcited by 5
  6. 2025Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairmentcited by 5
  7. 2024A Systematic Review of NLP for Dementia -- Tasks, Datasets and Opportunitiescited by 4
  8. 2024Performance Assessment of ChatGPT vs Bard in Detecting Alzheimer's Dementiacited by 3
  9. 2024Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detectioncited by 2
  10. 2025Speech-Based Cognitive Screening: A Systematic Evaluation of LLM Adaptation Strategiescited by 2
  11. 2024Explainable cognitive decline detection in free dialogues with a Machine Learning approach based on pre-trained Large Language Modelscited by 1
  12. 2022Exploring Hybrid and Ensemble Models for Multiclass Prediction of Mental Health Status on Social Mediacited by 0
1 more
  1. 2026Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detectioncited by 0