22 citations · 40 across the 12 of their papers we have counts for
4 papers · 1 filter
A knowledge-driven vowel-based approach of depression classification from speech using data augmentation
Kexin Feng, Theodora Chaspari
We propose a novel explainable machine learning (ML) model that identifies depression from speech, by modeling the temporal dependencies across utterances and utilizing the spectro…
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…
Predicting the meal macronutrient composition from continuous glucose monitors
Zepeng Huo, Bobak J. Mortazavi, Theodora Chaspari +3
Sustained high levels of blood glucose in type 2 diabetes (T2DM) can have disastrous long-term health consequences. An essential component of clinical interventions for T2DM is mon…