Voice Biomarkers · Scientific References
A working bibliography of peer-reviewed literature on vocal and acoustic biomarkers for health, organized from general field reviews through the underlying voice science, the technology that makes it possible, and the clinical conditions where it has been studied. Every entry below is a real, PubMed-indexed publication, linked directly to its PubMed record.
Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice.
Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations.
Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning.
Automated assessment of psychiatric disorders using speech: A systematic review.
Consensus-Based Definitions for Vocal Biomarkers: The International VOCAL Initiative.
Translating AI research into reality: summary of the 2025 voice AI Symposium and Hackathon.
Ethical Considerations for AI-Enabled Voice Analysis: Features of an Emerging Bioethics Literature.
The epistemic economy of vocal biomarker startups: a qualitative interview study of data practices and governance.
Voice and speech as digital biomarkers of mental health: a scoping review of clinical interpretability, data collection and translational readiness.
Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review.
Explainable and Interpretable AI for Voice and Speech Analysis in Clinical Care: Systematic Review.
Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions.
Voice disorders classification using machine learning: a scoping review.
Collection and Analysis of Repeated Speech Samples: Methodological Framework and Example Protocol.
Voice as a predictive signal: protocol for a scoping review of AI in early childhood development.
Vocal biomarkers for geriatric health assessment: a scoping review protocol.
Water limitation modifies vocal performance in California mice: implications for acoustic communication under environmental stress.
Mechanisms of speaker adaptation to semi-occluded vocal tract exercises: Insights from computational phonation modeling.
Mini-breaths and vocal-fry-like laryngeal register alleviate respiratory constraints on tokay (Gekko gecko) mating vocalizations.
Biomechanical Mechanisms of Vocal Fold Nodule and Polyp Formation: A Review.
The Effects of Preservation and Structural Rhinoplasty on Voice Parameters.
Principal dimensions of voice production and their role in vocal expression.
Voice actors show enhanced neural tracking of pitch, prosody perception, and music perception.
Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments.
Superior Communication of Positive Emotions Through Nonverbal Vocalisations Compared to Speech Prosody.
Muscular and neuronal control of voice production – forgotten findings, current concepts, and new developments.
Analysis of vibratory mode changes in symmetric and asymmetric activation of the canine larynx.
Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.
Predictions of fundamental frequency changes during phonation based on a biomechanical model of the vocal fold lamina propria.
Human brain activation during phonation and exhalation: common volitional control for two upper airway functions.
Insights on Modelling Physiological, Appraisal, and Affective Indicators of Stress using Audio Features.
Effects of Mechanical Vibration Stimulation of the Larynx on Voice Production.
Segmental vs phrase-level creak in Polish: An acoustic analysis.
The evolution of human speech: the role of enhanced breathing control.
Computational analysis of asymmetric thyroarytenoid and cricothyroid activation in human phonation.
The Effect of Foot Arch Morphology and Plantar Pressure Distribution on Craniovertebral Angle and Acoustic Voice Parameters Across Different Postures.
More than just a happy talk? Evidence for functional pitch and utterance length modifications in infant-, spouse-, and dog-directed communication.
Fathers' unmodulated prosody in child-directed speech.
Prosodic Differences in the Voices of Transgender and Cisgender Women: Self-Perception of Voice – An Auditory and Acoustic Analysis.
The Sound of Hypnotherapy: Identification of Paralinguistic Speech Features Using Acoustic Analysis and Deep Learning.
Cross-sectional stratification of fall-related vulnerability in Parkinson's disease through multimodal fusion of speech, gait, facial expression, and upper-limb movement.
VocaSense-X Framework: Advancing Voice Medicine Through Intelligent Diagnosis and Rehabilitation.
Emotionally engaged speech reveals acoustic markers of depression and suicide risk.
Demographic Confounding in Voice-Based Parkinson Disease Screening: Methodological Analysis of the Bridge2AI Voice Dataset.
Generating Alzheimer's narratives using large language models.
Exploring GPT-based models for depression detection in adolescents using naturalistic speech: A proof-of-concept study.
A frequency analysis of filterbank initialisation and noise augmentation for LEAF.
Explainable multimodal feature fusion networks for Parkinson's disease prediction.
Artificial intelligence-based speech error detection to differentiate primary progressive aphasia variants.
Parkinson's disease diagnosis using machine learning and multimodal biomarkers: A systematic review.
Development and clinical translation of smartphone-based digital biomarkers for Parkinson's disease: a structured review.
Generalization over accuracy: A cross-dataset, explainable, and federated learning framework for Parkinson's disease detection.
A novel multimodal AI framework for early diagnosis of idiopathic Parkinson's disease.
Prediction of Aspiration Risk by Using Vocal Biomarkers: Machine Learning Development and Validation Study.
Applications of Artificial Intelligence in Neurological Voice Disorders.
Multi-Modal Decentralized Hybrid Learning for Early Parkinson's Detection Using Voice Biomarkers and Contrastive Speech Embeddings.
R-SPEAK, an AI-Based Smartphone App to Enhance Communication in People With Expressive Aphasia: Qualitative Acceptability and Usability Study.
A neural architecture for imagined and overt speech motor dynamics.
Optimized Deep Learning for the Classification of Parkinson's Disease Based on Voice Features.
A Clinical AI-Based System (MoodMon) for Affective Disorders: Algorithm Development and Validation.
MoodMon: novel optimization of bipolar disorder monitoring through patient-driven voice parameter submission and AI technology.
Clinical speech AI for schizophrenia: Diagnostic accuracy of speech- and language-based digital biomarkers in a PRISMA-DTA systematic review and meta-analysis.
Artificial intelligence and hearing health: a global evidence review of biases and equity implications for Africa.
Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection.
Toward demographic robustness in digital patient twins: Addressing the gender data gap.
Voice-Based Screening of Depression and Anxiety Using Machine Learning and Deep Learning: A Scoping Review of Methods and Clinical Readiness.
The VOICE-DEP study protocol: Multimodal analysis of voice and speech during medical interviews to support diagnosis and longitudinal monitoring of major depressive disorder.
Validating objective and scalable speech markers of depression across two independent psychiatric cohorts.
Depression markers in speech: An approach based on tract variables dynamics.
Speech as a biomarker for supported diagnosis of major depressive disorder using self-supervised representations.
The Role of Voice Acoustics in Depression Assessment: Findings From Bibliometric Analysis, Literature Review, and Meta-Analysis.
Ecological Momentary Assessment and Voice-Informed Forecast and Detection for the Diagnosis of Major Depression.
Speech analysis for differentiating bipolar disorder and major depressive disorder during euthymic states.
A Decision Support System for Major Depressive Disorder Detection Using EMD and CNN-BiLSTM-Based Analysis of Human Voice.
Beyond acoustic features: Incorporating linguistic variables in automatic speech analysis for depression detection.
ML-based detection of depressive profile through voice analysis in WhatsApp audio messages of Brazilian Portuguese Speakers.
Gaborformer: A method for depression detection through hybrid acoustic feature extraction and fusion.
Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study.
Depression, speech intelligibility, and articulatory coordination.
Speech-derived acoustic biomarkers for depression: Comprehensive cross-section and longitudinal analyses in different cohorts.
The relationship between cognitive impairment and acoustic features in major depressive disorder: a longitudinal cohort study.
Voice of Mind, a Deep Learning Model for Depression and Anxiety Assessment From Acoustic and Lexical Vocal Biomarkers.
Unraveling the associations between voice pitch and major depressive disorder: a multisite genetic study.
Digital Markers for Passive Remote Monitoring of Bipolar Disorder: Systematic Review.
Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities.
Mood states recognition based on Mandarin speech and deep learning in patients with bipolar disorder.
Exploring Acoustic Correlates of Depression and Preliminary Screening Models Using XGBoost and SHAP.
Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study.
Affective Computing for Late-Life Mood and Cognitive Disorders.
Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.
Cross-sectional and longitudinal associations between anxiety and acoustic-prosodic markers in adolescents.
Automated Speech Analysis for Risk Detection of Depression, Anxiety, Insomnia, and Fatigue: Algorithm Development and Validation Study.
Feasibility of a Machine Learning-Based Smartphone Application in Detecting Depression and Anxiety in a Generally Senior Population.
Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood.
Recognizing anxiety and depression in cancer patients based on speech and facial expressions.
Stress measurement using speech: Recent advancements, validation issues, and ethical and privacy considerations.
Human Stress Detection: Cortisol Levels in Stressed Speakers Predict Voice-Based Judgments of Stress.
Individual differences in cortisol stress response predict increases in voice pitch during exam stress.
Aerodynamic and Acoustic Voice Measures Before and After an Acute Public Speaking Stressor.
The Fundamental Frequency of Voice as a Potential Stress Biomarker: A Systematic Review and Meta-Analysis.
Novel Deep Learning-Based Vocal Biomarkers for Stress Detection in Koreans.
Using Vocal Characteristics To Classify Psychological Distress in Adult Helpline Callers: Retrospective Observational Study.
Psychosocial Stress in the Chinese Community: Speech Analytics Through Linguistic and Acoustic Fusion Using Machine Learning.
Daily stress detection from real-life speeches using acoustic and semantic information.
Acoustic speech features in social comparison: how stress impacts the way you sound.
Voice Signatures of Momentary Psychological Stress in Real-Life Environments: Results from the Colive Voice Study.
Emotional Prosody Measurement (EPM): a voice-based evaluation method for psychological therapy effectiveness.
Using speech analysis in virtual agent conversations to differentiate PTSD patients from control participants.
An Emotion-Driven Vocal Biomarker-Based PTSD Screening Tool.
Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood.
Study protocol: how does parental stress measured by clinical scales and voice acoustic stress markers predict children's response to PTSD trauma-focused therapies?.
Comprehension of affective prosody in veterans with chronic posttraumatic stress disorder.
Study of agency in the discourse of women suffering from post-traumatic stress disorder in the aftermath of domestic violence.
Robust Detection of Parkinson's Disease Using Harvested Smartphone Voice Data: A Telemedicine Approach.
Investigating voice as a biomarker: Deep phenotyping methods for early detection of Parkinson's disease.
Transformer-based transfer learning on self-reported voice recordings for Parkinson's disease diagnosis.
An Explainable Ensemble and Deep Learning Framework for Accurate and Interpretable Parkinson's Disease Detection from Voice Biomarkers.
Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.
Vocal Biomarkers for Parkinson's Disease Classification Using Audio Spectrogram Transformers.
From prodromal stages to clinical trials: The promise of digital speech biomarkers in Parkinson's disease.
Speech and language biomarkers for Parkinson's disease prediction, early diagnosis and progression.
Voice Analysis to Differentiate the Dopaminergic Response in People With Parkinson's Disease.
Vocal Biomarkers for Parkinson's Disease Classification through Hybrid Feature Selection with Beluga Whale Optimization.
Explainable artificial intelligence to diagnose early Parkinson's disease via voice analysis.
Speech Biomarkers From Smartphone Calls Track Progression in REM Sleep Behavior Disorder and Parkinson's Disease.
Explainable machine learning for early detection of Parkinson's disease in aging populations using vocal biomarkers.
Machine learning-based classification of Parkinson's disease using acoustic features: Insights from multilingual speech tasks.
Machine Learning-Assisted Speech Analysis for Early Detection of Parkinson's Disease: A Study on Speaker Diarization and Classification Techniques.
Analysis of spontaneous speech in Parkinson's disease by natural language processing.
Utilizing speech analysis to differentiate progressive supranuclear palsy from Parkinson's disease.
Voice analysis in Parkinson's disease – a systematic literature review.
Gradient boosting for Parkinson's disease diagnosis from voice recordings.
Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.
Parkinson's disease or atypical parkinsonism? The importance of acoustic voice analysis in differential diagnosis of speech disorders.
Speech disorders in Parkinson's disease: early diagnostics and effects of medication and brain stimulation.
Vowel articulation in Parkinson's disease.
Automated speech analysis in early untreated Parkinson's disease: Relation to gender and dopaminergic transporter imaging.
Acoustic investigation of stress patterns in Parkinson's disease.
Speech acoustic indices for differential diagnosis between Parkinson's disease, multiple system atrophy and progressive supranuclear palsy.
Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.
Vocal Feature Changes for Monitoring Parkinson's Disease Progression – A Systematic Review.
Mixed kernel SVR addressing Parkinson's progression from voice features.
Ten Years of Research on Automatic Voice and Speech Analysis of People With Alzheimer's Disease and Mild Cognitive Impairment: A Systematic Review Article.
A systematic literature review of automatic Alzheimer's disease detection from speech and language.
Acoustic Speech Analysis in Alzheimer's Disease: A Systematic Review and Meta-Analysis.
An Overview of the ADReSS-M Signal Processing Grand Challenge on Multilingual Alzheimer's Dementia Recognition Through Spontaneous Speech.
Acoustic and Language Based Deep Learning Approaches for Alzheimer's Dementia Detection From Spontaneous Speech.
Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?.
Natural language processing techniques for studying language in pathological ageing: A scoping review.
Detecting Alzheimer's Disease Using Natural Language Processing of Referential Communication Task Transcripts.
How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease.
Enhancing dementia and cognitive decline detection with large language models and speech representation learning.
AI-based assessments of speech and language impairments in dementia.
Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability.
Linking silent pause locations in speech to amyloid and tau deposition in cognitively unimpaired individuals.
Automated detection of progressive speech changes in early Alzheimer's disease.
Natural speech markers of Alzheimer's disease co-pathology in Lewy body dementias.
Longitudinal observational cohort study: Speech for Intelligent cognition change tracking and DEtection of Alzheimer's Disease (SIDE-AD).
Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices.
Digital detection of Alzheimer's disease using smiles and conversations with a chatbot.
Speech digital biomarker combined with fluid biomarkers predict cognitive impairment through machine learning.
Screening for early Alzheimer's disease: enhancing diagnosis with linguistic features and biomarkers.
Cognitive and Structural Correlates of Conversational Speech Timing in Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease: Relevance for Early Detection Approaches.
Natural language processing-based classification of early Alzheimer's disease from connected speech.
Speech-based digital biomarkers for early etiological stratification of Alzheimer's disease and frontotemporal degeneration: a biomarker-confirmed prospective study.
Discrimination of mild cognitive impairment based on involuntary changes caused in voice elements.
Voice Markers of Lexical Access in Mild Cognitive Impairment and Alzheimer's Disease.
Voice quality and speech fluency distinguish individuals with Mild Cognitive Impairment from Healthy Controls.
Novel Screening Tool Using Non-linguistic Voice Features Derived from Simple Phrases to Detect Mild Cognitive Impairment and Dementia.
Reading and lexical-semantic retrieval tasks outperforms single task speech analysis in the screening of mild cognitive impairment and Alzheimer's disease.
A novel speech analysis algorithm to detect cognitive impairment in a Spanish population.
Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment.
Restoring Over-Attenuated Sustained Vowel Phonations in Smartphone Calls of COPD Patients Using U-Net and Speech Foundation Models.
Identification of individuals with COPD using biometric voice and cough sound features.
Feature Analysis of the Vowel [a:] in Individuals With Chronic Obstructive Pulmonary Disease and Healthy Controls.
Respiratory-Responsive Vocal Biomarker for Asthma Exacerbation Monitoring: Prospective Cohort Study.
Artificial Intelligence Powered Audiomics: The Futuristic Biomarker in Pulmonary Medicine – A State-of-the-Art Review.
Developing a multi-feature fusion model for exacerbation classification in asthma and COPD.
Maximum Phonation Times as Biomarkers of Lung Function.
Development and Validation of a Respiratory-Responsive Vocal Biomarker-Based Tool for Generalizable Detection of Respiratory Impairment: Independent Case-Control Studies in Multiple Respiratory Conditions Including Asthma, COPD, and COVID-19.
Respiratory Disease Detection: A Systematic Review of AI-Based Approaches, from Audio and Visual Unimodal Methods to Multimodal Integration.
On-device cough detection and respiratory disease classification enhanced by generative data augmentation.
A Generative AI-Based Framework for COVID-19 Screening from Cough Audio Signals.
Advanced COVID-19 detection using cough signals with space reconstruction and 3D deep convolutional neural networks.
Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm.
Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review.
Reliability of crowdsourced data and patient-reported outcome measures in cough-based COVID-19 screening.
An explainable COVID-19 detection system based on human sounds.
Design and development of hybrid optimization enabled deep learning model for COVID-19 detection with comparative analysis with DCNN, BIAT-GRU, XGBoost.
DKPNet41: Directed knight pattern network-based cough sound classification model for automatic disease diagnosis.
The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.
A systematic review on cough sound analysis for Covid-19 diagnosis and screening: is my cough sound COVID-19?.
Past and Trends in Cough Sound Acquisition, Automatic Detection and Automatic Classification: A Comparative Review.
Asthma Detection Research Based on Voice Signal Processing and Machine Learning.
Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.
Phonatory Symptoms and Acoustic Findings in Patients with Asthma: A Cross-Sectional Controlled Study.
Acoustic analysis in asthmatics and the influence of inhaled corticosteroid therapy.
Breathing and speech patterns for predictive modelling of exacerbations of asthma and COPD.
COVID-19 activity screening by a smart-data-driven multi-band voice analysis.
Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.
Respiratory sound-based AI screening of asthma and COPD via multi-feature fusion and CatBoost classification.
Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.
Voice Signal Characteristics Are Independently Associated With Coronary Artery Disease.
Non-invasive vocal biomarker is associated with pulmonary hypertension.
Guess What We Can Hear—Novel Voice Biomarkers for the Remote Detection of Disease.
Acoustic features are independently associated with heart failure and pulmonary hypertension.
Remote Speech Analysis in the Evaluation of Hospitalized Patients With Acute Decompensated Heart Failure.
Trends in voice characteristics in patients with heart failure (VENTURE) in Switzerland: Protocol for a longitudinal observational pilot study.
Vocal biomarkers in heart failure—design, rationale and baseline characteristics of the AHF-Voice study.
Remote monitoring in heart failure: artificial intelligence and the use of remote speech analysis to detect worsening heart failure events.
The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.
How voice biomarkers have been used in heart failure management: a scoping review.
The voice of decompensation: an explainable machine learning approach to assessing heart failure severity.
Speech Signal Parameters as Biomarkers for Remote Monitoring of Patients with Chronic Heart Failure.
When AI enters nursing practice: reflections based on a study using voice biomarkers in heart failure monitoring.
Voice recognition as an innovative method to identify and monitor heart failure – a review.
Multimodal deep learning for cardiovascular disease detection using pulse wave and vocal signals: a prediction model development and validation study.
Voice features and deep learning models for identifying acute decompensated heart failure.
Efficacy of a Voice Biomarker for the Prediction of Heart Failure Hospitalisation: Results from the Telemedical Interventional Management in Heart Failure III (TIM-HF3) Voice Study.
Non-invasive classification of stable HFpEF using a deep learning model trained on acoustic features of sustained vowels.
A pilot study on AI-based voice analysis for monitoring patients hospitalized with acute decompensated heart failure.
Daily Laryngeal Kinematics and Acoustics Throughout the Menstrual Cycle: A Longitudinal Case Study.
Longitudinal Changes in Pitch-Related Acoustic Characteristics of the Voice Throughout the Menstrual Cycle: Observational Study.
Blood Plasma Hormone-Level Influence on Vocal Function.
Fundamental Frequency Variations Across the Menstrual Cycle and the Use of an Oral Contraceptive Pill.
Vocal Acoustic and Auditory-Perceptual Characteristics During Fluctuations in Estradiol Levels During the Menstrual Cycle: A Longitudinal Study.
Menstrual Cycle, Vocal Performance, and Laryngeal Vascular Appearance: An Observational Study on 17 Subjects.
The Effect of Menstrual Cycle on Singing Voice: A Systematic Review.
Voice and speech changes in various phases of menstrual cycle.
Do women's voices provide cues of the likelihood of ovulation? The importance of sampling regime.
Testosterone-Related Voice Change in Cisgender Women: A Survey of Prescribers and Voice Clinicians.
Female Patients with Reinke's Edema: The Effect of Menopause Status on Voice-Related Disease Severity.
Effect of Hormonal Changes in Pre and Post-Menopausal Women Related Acoustical Voice Markers.
What Voice-Related Metrics Change With Menopause? A Systematic Review and Meta-Analysis Study.
Vocal Symptoms and Acoustic Findings in Menopausal Women in Comparison to Pre-menopause Women with Body Mass Index as a Confounding Variable.
Effect of Hormonal Replacement Therapy on Voice.
Functional Voice Testing Detects Early Changes in Vocal Pitch in Women During Testosterone Administration.
The impact of hormone therapy on vocal quality in postmenopausal women.
The impact of menopause on vocal quality.
Normal Pregnancy and Voice: A PRISMA-ScR Scoping Review of Laryngeal and Vocal Outcomes.
Pregnancy and the Singing Voice: A Survey of What Singers Report.
Effect of sex hormones on human voice physiology: from childhood to senescence.
Clinical Characteristics of Women With Low Vocal Pitch During Pregnancy.
Acoustic and aerodynamic measures of the voice during pregnancy.
A multimodal feature fusion model integrating voice acoustic features and early key risk factors for early screening of postpartum depression: a prospective short-term longitudinal observational study.
Multimodal Acoustic-Linguistic Machine Learning for Postpartum Depression Screening Using the Edinburgh Postnatal Depression Scale.
Dual-branch hierarchical fusion network for voice-based classification of type 2 diabetes mellitus using multi-vowel acoustic features.
Multi-Scale Cooperative Vowel Attention Strategy for Voice-Based Type 2 Diabetes Mellitus Detection.
Study on the characteristics analysis and recognition method of vowels in patients with type Ⅱ diabetes.
Voice changes associated with stress and distress in people living with diabetes: Results from the Colive Voice study.
Vocal Shimmer: A Potential Clinical Biomarker for Gestational Diabetes.
Listening to Hypoglycemia: Voice as a Biomarker for Detection of a Medical Emergency Using Machine Learning.
Voice-based prediction of prediabetes using classical machine learning models.
A Novel Machine Learning-Driven Voice and Clinical Biomarkers Framework for Robust Prediction of Type 2 Diabetes Mellitus.
Optimizing Voice Sample Quantity and Recording Settings for the Prediction of Type 2 Diabetes Mellitus: Retrospective Study.
Impact of Audio Data Compression on Feature Extraction for Vocal Biomarker Detection: Validation Study.
Exploring the impact of type II diabetes mellitus on voice quality.
Effect of Diabetes Mellitus Type 2 on Voice: A Systematic Review and Meta-Analysis.
Acoustic Analysis and Prediction of Type 2 Diabetes Mellitus Using Smartphone-Recorded Voice Segments.
Speech biomarkers of risk factors for vascular dementia in people with mild cognitive impairment.
The effect of type 1 diabetes mellitus on voice in pediatric patients.
Voice changes in reproductive disorders, thyroid disorders and diabetes: a review.
[Optimization of an integrated approach to voice correction for endocrinopathies (analytical review)].
Disease related changes in vocal parameters of patients with type 2 diabetes mellitus.
Instrumental Acoustic Voice Characteristics in Adults with Type 2 Diabetes.
Vocal characteristics in patients with type 2 diabetes mellitus.
Acoustic Features of Sustained Phonation for Schizophrenia Classification: A Feasibility Study.
Speech-based relapse prediction in psychosis using explainable AI: Protocol for the international multicentre observational TRUSTING study.
An integrative NLP framework identifies multilevel linguistic phenotypes of schizophrenia across tasks.
Online speech assessment of the psychotic spectrum: Exploring the relationship between overlapping acoustic markers of schizotypy, depression and anxiety.
Vocal acoustic features may be objective biomarkers of negative symptoms in schizophrenia: A cross-sectional study.
Speech analysis and speech emotion recognition in mental disease: a scoping review.
Acoustic analysis of vowel production in adults with autism spectrum disorder: beyond the notion of a unitary autistic voice.
Unstable or Stable? Prosodic Features and Voice Quality in Autism Spectrum Disorder: A Systematic Review and Meta-analysis.
Quantifying vocal subsystems of adults with minimally verbal autism spectrum disorder.
Voice acoustics allow classifying autism spectrum disorder with high accuracy.
Acoustic Exaggeration Enhances Speech Discrimination in Young Autistic Children.
Different in different ways: A network-analysis approach to voice and prosody in Autism Spectrum Disorder.
Toward a cumulative science of vocal markers of autism: A cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children.
Feasibility study on a noninvasive assessment of ALS patient emotional state.
Biomechanical Voice Parameters as Potential Biomarkers for Phenotype Differentiation in Amyotrophic Lateral Sclerosis: A Cross-Sectional Study.
Acoustic Voice Analysis as a Useful Tool to Discriminate Different ALS Phenotypes.
Acoustic Change Over Time in Spastic and/or Flaccid Dysarthria in Motor Neuron Diseases.
Characterizing vocal tremor in progressive neurological diseases via automated acoustic analyses.
Discriminating Relapsing-Remitting From Progressive Multiple Sclerosis Using Multidimensional Speech Biomarkers: An Independent Cohort Validation Study.
Association Between Acoustic Speech Measures and Disability in Multiple Sclerosis: A Systematic Review and Meta-analysis.
Screening speech disorders in progressive neurological diseases via long-term average spectrum.
Through the Speech and Vocal Signals Hidden Secrets: An Explainable Methodology for Neurological Diseases Early Detection.
What speech can tell us: A systematic review of dysarthria characteristics in Multiple Sclerosis.
Language biomarker screening using AI: a transdiagnostic approach to the brain.
Attention-based Deep Feature Fusion for Automated Dysarthria Severity Classification: A Speech-based Computational Functional Marker Relevant to Neurovascular and Neurodegenerative Conditions.
Dysarthria associated with traumatic brain injury: speaking rate and emphatic stress.
Cognitive task demands and discourse performance after traumatic brain injury.
Incidence and clinical presentation of dysarthria and dysphagia in the acute setting following paediatric traumatic brain injury.
From voice biomarkers to telemedicine screening: developing and evaluating a voice-based AI model for laryngeal lesion detection using the Bridge2AI-Voice dataset.
Voice as a biomarker: exploratory analysis for benign and malignant vocal fold lesions.
Early Detection of Glottic Cancer Through Machine Learning and Acoustic Voice Analysis: A Systematic Review.
Machine learning-powered audio-omics processing method as an auxiliary diagnostic approach for advanced nasopharyngeal carcinoma.
Acoustic Biomarkers Derived From Computerized Voice Analysis for Predicting Anterior Commissure Involvement and Survival in Laryngeal Carcinoma.
Chemoradiotherapy versus transoral laser microsurgery for early T-stage (cT1-T2) hypopharyngeal cancer: A prospective randomized pilot study.
Analysis of clinical efficacy and quality of life in hypopharyngeal cancer patients undergoing laryngeal-preserving surgery.
Longitudinal correlations of subjective, functional, and objective voice parameters following radiotherapy for early glottic carcinoma.
Long-Term Voice Outcomes After Trans-Oral Resection of Early Glottis Carcinoma.
Functional Voice Restoration After Laryngeal Transplantation: A Multidisciplinary Protocol and Longitudinal Outcomes.
Muscle Tension Dysphonia: A Sequeale of Chemoradiotherapy in Patients of Head and Neck Cancer.
Voice outcomes in patients with advanced laryngeal and hypopharyngeal cancer treated with chemo-radiotherapy.
Acoustic analysis of voice in nonlaryngeal head and neck cancer patients post chemoradiotherapy.
Pre- and posttreatment voice and speech outcomes in patients with advanced head and neck cancer treated with chemoradiotherapy: expert listeners' and patient's perception.
Voice and swallowing in patients enrolled in a larynx preservation trial.
Vocal fundamental frequency measures as a reflection of tumor response to chemotherapy in patients with advanced laryngeal cancer.
Beyond the jaw: vocal, oropharyngeal and cognitive-linguistic biomarkers for precision pain phenotyping in TMD.
Blood Lactate as a Metabolic Biomarker of Anaerobic Vocal Capacity: A Pilot Study.
Harmonic-to-noise ratio as speech biomarker for fatigue: K-nearest neighbour machine learning algorithm.
Sleep deprivation detected by voice analysis.
A rapid, non-invasive method for fatigue detection based on voice information.
Measuring Stress in Health Professionals Over the Phone Using Automatic Speech Analysis During the COVID-19 Pandemic: Observational Pilot Study.
This bibliography was compiled from PubMed/MEDLINE search results and is provided for scientific and clinical reference. Inclusion of a study does not constitute endorsement of its methodology or conclusions by Amplifier Health, and this list does not represent clinical validation of any Amplifier Health product. Categorization reflects the primary focus of each study; several studies span more than one category. This page is updated periodically as new literature is published.