9 papers
TorchDIVA: An Extensible Computational Model of Speech Production built on an Open-Source Machine Learning Library
Sean Kinahan, Julie Liss, Visar Berisha
The DIVA model is a computational model of speech motor control that combines a simulation of the brain regions responsible for speech production with a model of the human vocal tr…
Consonant-Vowel Transition Models Based on Deep Learning for Objective Evaluation of Articulation
Vikram C. Mathad, Julie M. Liss, Kathy Chapman +2
Spectro-temporal dynamics of consonant-vowel (CV) transition regions are considered to provide robust cues related to articulation. In this work, we propose an objective measure of…
A Deep Learning Algorithm for Objective Assessment of Hypernasality in Children with Cleft Palate
Vikram C. Mathad, Nancy Scherer, Kathy Chapman +2
Objectives: Evaluation of hypernasality requires extensive perceptual training by clinicians and extending this training on a large scale internationally is untenable; this compoun…
Robust Estimation of Hypernasality in Dysarthria with Acoustic Model Likelihood Features
Michael Saxon, Ayush Tripathi, Yishan Jiao +2
Hypernasality is a common characteristic symptom across many motor-speech disorders. For voiced sounds, hypernasality introduces an additional resonance in the lower frequencies an…
A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders
Rohit Voleti, Julie M. Liss, Visar Berisha
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 o…
Objective Assessment of Social Skills Using Automated Language Analysis for Identification of Schizophrenia and Bipolar Disorder
Rohit Voleti, Stephanie Woolridge, Julie M. Liss +3
Several studies have shown that speech and language features, automatically extracted from clinical interviews or spontaneous discourse, have diagnostic value for mental disorders…