ArticleNPJ schizophrenia2020
Using machine learning of computerized vocal expression to measure blunted vocal affect and alogia.
Article in NPJ schizophrenia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Voice Patterns as Markers of Schizophrenia: Building a Cumulative Generalizable Approach Via a Cross-Linguistic and Meta-analysis Based Investigation.Schizophrenia bulletin · 2023Pooled it
- Humanizing "multimodal" digital phenotyping of serious mental illness.Journal of psychopathology and clinical science · 2026Article
- Analyzing Generative AI and Machine Learning in Auto-Assessing Schizophrenia's Negative Symptoms.Schizophrenia bulletin · 2026Article
- Vocal Markers of Schizophrenia: Assessing the Generalizability of Machine Learning Models and Their Clinical Applicability.Schizophrenia bulletin · 2026Article
- Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.Translational psychiatry · 2026Article
- Environmental deprivation is associated with reward processing impairments and negative symptoms in schizophrenia.Schizophrenia research · 2025Article
- Article
- Rationale and Challenges for a New Instrument for Remote Measurement of Negative Symptoms.Schizophrenia bulletin open · 2024Review
- The Influence of Greenspace Exposure on Affect in People With and Those Without Schizophrenia: Exploratory Study.JMIR formative research · 2023Article
- A Narrative Review of Speech and EEG Features for Schizophrenia Detection: Progress and Challenges.Bioengineering (Basel, Switzerland) · 2023Review
- Language Analytics for Assessment of Mental Health Status and Functional Competency.Schizophrenia bulletin · 2023Article
- Correlates of Social Isolation in Forensic Psychiatric Patients with Schizophrenia Spectrum Disorders: An Explorative Analysis Using Machine Learning.International journal of environmental research and public health · 2023Article
- Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis.Early intervention in psychiatry · 2023Article
- Automated analysis of speech as a marker of sub-clinical psychotic experiences.Frontiers in psychiatry · 2023Review
- Identifying psychiatric manifestations in schizophrenia and depression from audio-visual behavioural indicators through a machine-learning approach.Schizophrenia (Heidelberg, Germany) · 2022Article
- Audio Recording Patient-Nurse Verbal Communications in Home Health Care Settings: Pilot Feasibility and Usability Study.JMIR human factors · 2022Article
- High Predictive Accuracy of Negative Schizotypy With Acoustic Measures.Clinical psychological science : a journal of the Association for Psychological Science · 2022Article
- Avolition as the core negative symptom in schizophrenia: relevance to pharmacological treatment development.NPJ schizophrenia · 2021Review
- Mechanisms Underlying Motivational Dysfunction in Schizophrenia.Frontiers in behavioral neuroscience · 2021Review
- Acoustic speech features are associated with late-life depression and apathy symptoms: Preliminary findings.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Negative symptoms are a transdiagnostic feature of serious mental illness (SMI) that can be potentially "digitally phenotyped" using objective vocal analysis. In prior studies, vocal measures show low convergence with clinical ratings, potentially because analysis has used small, constrained acoustic feature sets. We sought to evaluate (1) whether clinically rated blunted vocal affect (BvA)/alogia could be accurately modelled using machine learning (ML) with a large feature set from two separate tasks (i.e., a 20-s "picture" and a 60-s "free-recall" task), (2) whether "Predicted" BvA/alogia (computed from the ML model) are associated with demographics, diagnosis, psychiatric symptoms, and cognitive/social functioning, and (3) which key vocal features are central to BvA/Alogia ratings. Accuracy was high (>90%) and was improved when computed separately by speaking task. ML scores were associated with poor cognitive performance and social functioning and were higher in patients with schizophrenia versus depression or mania diagnoses. However, the features identified as most predictive of BvA/Alogia were generally not considered critical to their operational definitions. Implications for validating and implementing digital phenotyping to reduce SMI burden are discussed.
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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.