no code implementations • 11 Mar 2022 • Rahil Parikh, Nadee Seneviratne, Ganesh Sivaraman, Shihab Shamma, Carol Espy-Wilson
We used U. of Wisconsin X-ray Microbeam (XRMB) database of clean speech signals to train a feed-forward deep neural network (DNN) to estimate articulatory trajectories of six tract variables.
no code implementations • 13 Feb 2022 • Nadee Seneviratne, Carol Espy-Wilson
The multimodal system is developed by combining embeddings from the session-level audio model and the HAN text model
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 9 Apr 2021 • Nadee Seneviratne, Carol Espy-Wilson
The ACFs derived from the vocal tract variables (TVs) are used to train a dilated Convolutional Neural Network based depression classification model to obtain segment-level predictions.
no code implementations • 13 Nov 2020 • Nadee Seneviratne, Carol Espy-Wilson
We show that ACFs derived from Vocal Tract Variables (TVs) show promise as a robust set of features for depression detection.