TalTech Systems for the PROCESS Signal Processing Grand Challenge

Erik Illaste, Tanel Alumäe

Abstract: The PROCESS Challenge aims to detect cognitive decline, including early stages like mild cognitive impairment, through spontaneous speech. This paper describes TalTech’s systems prepared for the challenge that applied machine learning models incorporating multimodal features to address both regression and classification tasks. For regression, the Lasso model achieved an RMSE of 2.54 on the test set, achieving 2nd place in the challenge. For classification, the XGBoost model achieved a macro F1 score of 0.61, placing 6th. These results demonstrate the potential of integrating diverse speech-based features and predictive modeling for scalable, early detection of cognitive decline.

External IDs:dblp:conf/icassp/IllasteA25