10 citations · 21 across the 8 of their papers we have counts for
10 papers
Towards clinical adoption of voice and speech as measures of health: the need for harmonization
Nicholas Cummins, Vikram Ramanarayanan, Daniel Low +9
Speech and voice are multidimensional signals that capture both communicative intent and underlying physiological processes, providing a unique, non-invasive window into health. An…
Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity
Anastasiia Tokareva, Judith Dineley, Zoe Firth +19
Background: Remotely captured spoken language could provide objective, regular indicators of depression symptom severity. However, research to date has largely used non-clinical, c…
A methodological framework and exemplar protocol for the collection and analysis of repeated speech samples
Nicholas Cummins, Lauren L. White, Zahia Rahman +8
Speech and language biomarkers have the potential to be regular, objective assessments of symptom severity in several health conditions, both in-clinic and remotely using mobile de…
Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model
Yuezhou Zhang, Amos A Folarin, Judith Dineley +25
Language use has been shown to correlate with depression, but large-scale validation is needed. Traditional methods like clinic studies are expensive. So, natural language processi…
Towards robust paralinguistic assessment for real-world mobile health (mHealth) monitoring: an initial study of reverberation effects on speech
Judith Dineley, Ewan Carr, Faith Matcham +4
Speech is promising as an objective, convenient tool to monitor health remotely over time using mobile devices. Numerous paralinguistic features have been demonstrated to contain s…
HEAR4Health: A blueprint for making computer audition a staple of modern healthcare
Andreas Triantafyllopoulos, Alexander Kathan, Alice Baird +20
Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalen…
Detecting the Severity of Major Depressive Disorder from Speech: A Novel HARD-Training Methodology
Edward L. Campbell, Judith Dineley, Pauline Conde +7
Major Depressive Disorder (MDD) is a common worldwide mental health issue with high associated socioeconomic costs. The prediction and automatic detection of MDD can, therefore, ma…
Fitbeat: COVID-19 Estimation based on Wristband Heart Rate
Shuo Liu, Jing Han, Estela Laporta Puyal +26
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilise…
Remote smartphone-based speech collection: acceptance and barriers in individuals with major depressive disorder
Judith Dineley, Grace Lavelle, Daniel Leightley +22
The ease of in-the-wild speech recording using smartphones has sparked considerable interest in the combined application of speech, remote measurement technology (RMT) and advanced…
Voice command generation using Progressive Wavegans
Thomas Wiest, Nicholas Cummins, Alice Baird +3
Generative Adversarial Networks (GANs) have become exceedingly popular in a wide range of data-driven research fields, due in part to their success in image generation. Their abili…