22 citations · 40 across the 12 of their papers we have counts for
5 papers · 1 filter
Robust and Explainable Depression Identification from Speech Using Vowel-Based Ensemble Learning Approaches
Kexin Feng, Theodora Chaspari
This study investigates explainable machine learning algorithms for identifying depression from speech. Grounded in evidence from speech production that depression affects motor co…
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationships
Kexin Feng, Jacqueline B. Duong, Kayla E. Carta +4
We design a metric learning approach that aims to address computational challenges that yield from modeling human outcomes from ambulatory real-life data. The proposed metric learn…
Toward Knowledge-Driven Speech-Based Models of Depression: Leveraging Spectrotemporal Variations in Speech Vowels
Kexin Feng, Theodora Chaspari
Psychomotor retardation associated with depression has been linked with tangible differences in vowel production. This paper investigates a knowledge-driven machine learning (ML) m…
Few-shot Learning in Emotion Recognition of Spontaneous Speech Using a Siamese Neural Network with Adaptive Sample Pair Formation
Kexin Feng, Theodora Chaspari
Speech-based machine learning (ML) has been heralded as a promising solution for tracking prosodic and spectrotemporal patterns in real-life that are indicative of emotional change…
An adversarial learning framework for preserving users' anonymity in face-based emotion recognition
Vansh Narula, Zhangyang, Wang +1
Image and video-capturing technologies have permeated our every-day life. Such technologies can continuously monitor individuals' expressions in real-life settings, affording us ne…