People | Locations | Statistics |
---|---|---|
Naji, M. |
| |
Motta, Antonella |
| |
Aletan, Dirar |
| |
Mohamed, Tarek |
| |
Ertürk, Emre |
| |
Taccardi, Nicola |
| |
Kononenko, Denys |
| |
Petrov, R. H. | Madrid |
|
Alshaaer, Mazen | Brussels |
|
Bih, L. |
| |
Casati, R. |
| |
Muller, Hermance |
| |
Kočí, Jan | Prague |
|
Šuljagić, Marija |
| |
Kalteremidou, Kalliopi-Artemi | Brussels |
|
Azam, Siraj |
| |
Ospanova, Alyiya |
| |
Blanpain, Bart |
| |
Ali, M. A. |
| |
Popa, V. |
| |
Rančić, M. |
| |
Ollier, Nadège |
| |
Azevedo, Nuno Monteiro |
| |
Landes, Michael |
| |
Rignanese, Gian-Marco |
|
Wagner, Michael
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (7/7 displayed)
- 2023Matching the photocurrent of 2‐terminal mechanically‐stacked perovskite/organic tandem solar modules by varying the cell widthcitations
- 2023Electrochemical Conversion of Cu Nanowire Arrays into Metal-Organic Frameworks HKUST-1citations
- 2018Biodegradation of synthetic polymers in soilscitations
- 2018Sustainable conversion of lignocellulose to high-purity, highly crystalline flake potato graphite.citations
- 2018Establishing a Rodent Model of Ventricular Fibrillation Cardiac Arrest With Graded Histologic and Neurologic Damage With Different Cardiac Arrest Durationscitations
- 2016Cross-Cultural Depression Recognition from Vocal Biomarkerscitations
- 2014NanoSIMS combined with fluorescence microscopy as a tool for subcellular imaging of isotopically labeled platinum-based anticancer drugscitations
Places of action
Organizations | Location | People |
---|
document
Cross-Cultural Depression Recognition from Vocal Biomarkers
Abstract
No studies have investigated cross-cultural and cross-language characteristics of depressed speech. We investigated the generalisability of a vocal biomarker-based approach to depression detection in clinical interviews recorded in three countries (Australia, the USA and Germany), two languages (German and English) and different accents (Australian and American). Several approaches to training and testing within and between datasets were evaluated.Using the same experimental protocol separately within each dataset, (cross-classification) accuracy was high. Combining datasets, high accuracy was high again and consistent across language, recording environment, and culture. Training and testing between datasets, however, attenuated accuracy. These finding emphasize the importance of heterogeneous training sets for robust depression detection.