A5003384228- Voice and Speech Disorders
- Speech Recognition and Synthesis
- Dysphagia Assessment and Management
- Music and Audio Processing
- Tracheal and airway disorders
- Speech and Audio Processing
- Artificial Intelligence in Healthcare and Education
- Cleft Lip and Palate Research
- Speech and dialogue systems
- Machine Learning in Healthcare
- AI in cancer detection
- COVID-19 diagnosis using AI
- Neurological disorders and treatments
- Radiomics and Machine Learning in Medical Imaging
- Craniofacial Disorders and Treatments
- Ear and Head Tumors
- Anesthesia and Sedative Agents
- Vasculitis and related conditions
- Digital Communication and Language
- Phonetics and Phonology Research
- Atherosclerosis and Cardiovascular Diseases
- Respiratory and Cough-Related Research
- Anesthesia and Pain Management
- Risk Perception and Management
- Head and Neck Cancer Studies
Vanderbilt University Medical Center
2017-2025
Vanderbilt University
2016-2020
Cincinnati Children's Hospital Medical Center
2014-2019
University of Cincinnati
2014-2019
Spoof speech can be used to try and fool speaker verification systems that determine the identity of based on voice characteristics. This paper compares popular learnable front-ends this task. We categorize by defining two generic architectures then analyze filtering stages both types in terms learning constraints. pro-pose replacing fixed filterbanks with a layer better adapt anti-spoofing tasks. The proposed FastAudio front-end is tested back-ends measure performance Logical Access track...
Hypernasality, a hallmark of velopharyngeal insufficiency (VPI), is speech disorder with significant psychosocial and functional implications. Conventional diagnostic methods rely heavily on specialized expertise equipment, posing challenges in resource-limited settings. This study explores the application OpenAI's Whisper model for automated hypernasality detection, offering scalable efficient alternative to traditional approaches. The was adapted binary classification by replacing its...
Background: Even after palatoplasty, the incidence of velopharyngeal dysfunction (VPD) can reach 30%; however, these estimates arise from high-income countries (HICs) where speech-language pathologists (SLP) are part standardized cleft teams. The VPD burden in low- and middle-income (LMICs) is unknown. This study aims to develop a machine-learning model that detect presence using audio samples alone. Methods: Case control were obtained institutional publicly available sources. A was built...
Objectives/Hypothesis Vocal fold scar is a major cause of dysphonia, and optimal treatments do not currently exist. Small intestinal submucosa (SIS) biomaterial developed for the treatment variety pathologies. The purpose this study was to investigate effects SIS implantation on tissue remodeling in scarred vocal folds using routine staining, immunohistochemistry, high‐speed videoendoscopy (HSV). Study Design Prospective, blinded group analysis. Methods Thirteen New Zealand White rabbits...
Acoustic analysis of voice has the potential to expedite detection and diagnosis disorders. Applying an image-based, neural-network approach analyzing acoustic signal may be effective means for detecting differentially diagnosing The purpose this study is provide a proof-of-concept that embedded data within human phonation can accurately efficiently decoded with deep learning neural network differentiate between normal disordered voices.Acoustic recordings from 10 vocally-healthy speakers,...
Purpose Videostroboscopy (VS) uses an indirect physiological signal to predict the phase of vocal fold vibratory cycle for sampling. Simulated stroboscopy (SS) extracts glottal directly from changing area in high-speed videoendoscopy (HSV) image sequence. The purpose this study is determine reliability SS relative VS clinical assessment function patients with mass lesions. Methods and recordings were obtained 28 lesions before after phonomicrosurgery 17 controls who vocally healthy. Two...
Objective Voice as a health biomarker using artificial intelligence (AI) is gaining momentum in research. The noninvasiveness of voice data collection through accessible technology (such smartphones, telehealth, and ambient recordings) or within clinical contexts means AI may help address disparities promote the inclusion marginalized communities. However, development AI-ready datasets free from bias discrimination complex task. objective this study to better understand perspectives engaged...
Accuracy and validity of voice AI algorithms rely on substantial quality data. Although commensurable amounts data are captured daily in centers across North America, there is no standardized protocol for acoustic management, which limits the usability these datasets artificial intelligence (AI) research.
Research in the past several years has boosted performance of automatic speaker verification systems and countermeasure to deliver low Equal Error Rates (EERs) on each system. However, research joint optimization both is still limited. The Spoofing-Aware Speaker Verification (SASV) 2022 challenge was proposed encourage development integrated SASV with new metrics evaluate model performance. This paper proposes an ensemble-free end-to-end solution, known as Spoof-Aggregated-SASV (SA-SASV)...
New Zealand white rabbits (Oryctolagus cuniculus) are an established in vivo model for the study of structural and functional consequences vocal-fold vibration. Research design requires invasive laryngotracheal procedures, presence laryngospasms or pain responses (or both) hinder phonation-related data collection. Published anesthesia regimens report respiratory depression muscle tone changes have been unsuccessful mitigating autonomic laryngeal our protocol. Infusion ketamine hydrochloride...
The purpose of this study was to quantitatively compare the effectiveness unilateral and bilateral botulinum toxin A (BTX-A) injections for mitigating undesirable weak/breathy voice quality dysphagia patients with adductor spasmodic dysphonia and/or essential tremor (ETV).
The world of voice biomarkers is rapidly evolving thanks to the use artificial intelligence (AI) allowing large-scale analysis voice, speech, and respiratory sound data. Bridge2AI-Voice project aims build a large-scale, ethically sourced, diverse database human voices linked health information help fuel Voice AI research, dubbed Audiomics. current paper describes development protocols data acquisition across 4 different adult cohorts disease (voice, respiratory, neurodegenerative diseases,...
Present the state-of-the-art overview of laryngeal pacing for treatment bilateral vocal fold paralysis. A minimally invasive unilateral system and a fully implantable are currently in clinical trials. The relative advantages disadvantages each discussed.Research functional electrical stimulation reanimation posterior cricoarytenoid muscle has successfully translated from animal models to human trials pacing. Current findings suggest humans significantly improves ventilation but only...
Background: Even after palatoplasty, the incidence of velopharyngeal dysfunction (VPD) can reach 30%; however, these estimates arise from high-income countries (HICs) where speech-language pathologists are part standardized cleft teams. The VPD burden in low- and middle-income (LMICs) is unknown. This study aims to develop a machine learning model that detect presence using audio samples alone. Methods: Case control were obtained by institutional publicly available sources. A was built...
Objective: The validity of objective measures derived from high-speed videoendoscopy (HSV) depends, among other factors, on the spatial segmentation. Evaluation segmentation requires existence reliable ground truths. This study presents a framework for creating truth with sub-pixel resolution and then evaluates its performance. Method: proposed is three-stage process. First, three laryngeal imaging experts performed task. Second, regions high discrepancies between were determined overlaid...