Temporal features highlight cognitive subtypes in Mild Cognitive Impairment and differentiate between memory and executive function issues. These features show diagnostic promise in machine learning contexts.
The study evaluated the accuracy of automatic speech recognition (ASR) software against manual scores in memory clinic assessments. The ASR showed high agreement with manual scores, and the phone-based tests effectively differentiated between subjective cognitive decline (SCD) and mild cognitive impairment (MCI).
Poster presented at the International Congress of Parkinson’s Disease and Movement Disorders. Copenhagen, 2023.
Tröger, J., Baltes, J., Baykara, E., Kasper, E., Kring, M., Linz, N., Robin, J., Schäfer, S., Schneider, A. & Hermann, A. (2023).Published in: Amyotrophic Lateral
The study aimed to predict depression severity using speech features during dialogues with a virtual avatar. Results showed that speech analysis can detect signs of depression, with the potential to enhance early interventions using virtual agents.
We will be presenting at the 9th Joint ECTRIMS-ACTRIMS Meeting, which will take place from October 11 to October 13, 2023 in Milan, Italy.
Schäfer, S., Mallick, E., Schwed, L., König, A., Zhao, J., Linz, N., Bodin, T. H., Skoog, J., Possemis, N., ter Huurne, D., Zettergren, A., Kern,
ter Huurne, D., Ramakers, I., Possemis, N., Banning, L., Gruters, A., Van Asbroeck, S., König, A., Linz, N., Tröger, J., Langel, K., Verhey, F., &
König, A., Linz, N., Baykara, E., Tröger, J., Ritchie, C., Saunders, S., Teipel, S., Köhler, S., Sánchez-Benavides, G., Grau-Rivera, O., Gispert, J. D., Palmqvist, S.,
König, A., Tröger, J., Mallick, E., Mina, M., Linz, N., Wagnon, C., Karbach, J., Kuhn, C., & Peter, J. (2022). Detecting subtle signs of depression