The invention is a method for automatic detection of
neurocognitive impairment, comprising,generating, in a segmentation and
labelling step (11), a labelled segment series (26) from a speech sample (22) using a
speech recognition unit (24); andgenerating from the labelled segment series (26), in an acoustic parameter calculation step (12), acoustic parameters (30) characterizing the speech sample (22).The method is characterised bydetermining, in a probability analysis step (14), in a particular temporal division of the speech sample (22), respective probability values (38) corresponding to silent pauses, filled pauses and any types of pauses for respective temporal intervals thereof;calculating, in an additional parameter calculating step (15), a
histogram by generating an additional
histogram data set (42) from the determined probability values (38) by dividing a probability domain into subdomains and aggregating durations of the temporal intervals corresponding to the probability values falling into the respective subdomains; andgenerating, in an evaluation step (13), decision information (34) by feeding the acoustic parameters (30) and the additional
histogram data set (42) into an evaluation unit (32), the evaluation unit (32) using a
machine learning
algorithm.The invention is furthermore
data processing system, a
computer program product and a computer-readable storage medium for carrying out the method.