ArticleIEEE journal of selected topics in signal processing2020
A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders.
Article in IEEE journal of selected topics in signal processing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.
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Who cites it
55 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Voice Analysis for Neurological Disorder Recognition-A Systematic Review and Perspective on Emerging Trends.Frontiers in digital health · 2022Pooled it
- Artificial Intelligence, Speech, and Language Processing Approaches to Monitoring Alzheimer's Disease: A Systematic Review.Journal of Alzheimer's disease : JAD · 2020Pooled it
- Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.International journal of language & communication disordersPooled it
- Reading between the lines: Combining pause dynamics and semantic coherence for automated assessment of thought disorder.Neuropsychologia · 2026Article
- Vocal Markers of Schizophrenia: Assessing the Generalizability of Machine Learning Models and Their Clinical Applicability.Schizophrenia bulletin · 2026Article
- Linking speech patterns to brain structure in affective and psychotic disorders: an integrative natural language processing approach.Molecular psychiatry · 2026Article
- Assessment of Language Impairments Towards Identifying Markers for Early Diagnosis of Pathological Cognitive Decline.Behavioral sciences (Basel, Switzerland) · 2026Review
- Linking spontaneous speech, cognition, and psychopathology across affective and psychotic disorders: A network approach.European psychiatry : the journal of the Association of European Psychiatrists · 2026Article
- Development and validation of a machine learning model to detect psychiatric symptoms in Huntington's disease using speech analysis.PloS one · 2026Article
- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- Speech features as potential objective assessment indicators in schizophrenia patients with violence-related symptoms.Frontiers in psychiatry · 2026Article
- Listening for Alzheimer's clues: machine learning analysis of multidomain speech features for cognitive impairment screening.Frontiers in aging neuroscience · 2026Article
- Article
- Revealing Hidden Cognitive Language Patterns in Brain Injury: Can Modifiers and Function Words Play a Role in Neuroplasticity?Brain sciences · 2025Article
- I speak Tele outlines the design of a digitized dysarthria assessment.Scientific reports · 2025Article
- Listening to the Mind: Integrating Vocal Biomarkers into Digital Health.Brain sciences · 2025Article
- Everyday Language and Cognitive Functioning in Late Life.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation.Bioengineering (Basel, Switzerland) · 2025Article
- Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders.Journal of medical Internet research · 2025Article
- Sex differences in PTSD speech biomarkers assessed by virtual agent-induced conversations.Frontiers in psychology · 2025Article
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3 authors.
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Abstract
It is widely accepted that information derived from analyzing speech (the acoustic signal) and language production (words and sentences) serves as a useful window into the health of an individual's cognitive ability. In fact, most neuropsychological testing batteries have a component related to speech and language where clinicians elicit speech from patients for subjective evaluation across a broad set of dimensions. With advances in speech signal processing and natural language processing, there has been recent interest in developing tools to detect more subtle changes in cognitive-linguistic function. This work relies on extracting a set of features from recorded and transcribed speech for objective assessments of speech and language, early diagnosis of neurological disease, and tracking of disease after diagnosis. With an emphasis on cognitive and thought disorders, in this paper we provide a review of existing speech and language features used in this domain, discuss their clinical application, and highlight their advantages and disadvantages. Broadly speaking, the review is split into two categories: language features based on natural language processing and speech features based on speech signal processing. Within each category, we consider features that aim to measure complementary dimensions of cognitive-linguistics, including language diversity, syntactic complexity, semantic coherence, and timing. We conclude the review with a proposal of new research directions to further advance the field.
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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.