96 citations · 280 across the 33 of their papers we have counts for
9 papers · 1 filter
Requirements for Mass Adoption of Assistive Listening Technology by the General Public
Thomas B. Kaufmann, Mehdi Foroogozar, Julie Liss +1
Assistive listening systems (ALSs) dramatically increase speech intelligibility and reduce listening effort. It is very likely that essentially everyone, not only individuals with…
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…
Triplet Network with Attention for Speaker Diarization
Huan Song, Megan Willi, Jayaraman J. Thiagarajan +2
In automatic speech processing systems, speaker diarization is a crucial front-end component to separate segments from different speakers. Inspired by the recent success of deep ne…
Investigating the role of L1 in automatic pronunciation evaluation of L2 speech
Ming Tu, Anna Grabek, Julie Liss +1
Automatic pronunciation evaluation plays an important role in pronunciation training and second language education. This field draws heavily on concepts from automatic speech recog…
Simulating dysarthric speech for training data augmentation in clinical speech applications
Yishan Jiao, Ming Tu, Visar Berisha +1
Training machine learning algorithms for speech applications requires large, labeled training data sets. This is problematic for clinical applications where obtaining such data is…
A Discriminative Acoustic-Prosodic Approach for Measuring Local Entrainment
Megan M. Willi, Stephanie A. Borrie, Tyson S. Barrett +2
Acoustic-prosodic entrainment describes the tendency of humans to align or adapt their speech acoustics to each other in conversation. This alignment of spoken behavior has importa…