Abstract: A dysarthria detection method includes an obtaining step and a detecting step. In the obtaining step, voice information regarding voice uttered by a subject is obtained. In the detecting step, it is detected whether the subject has dysarthria, based on an output result obtained by inputting the voice information obtained in the obtaining step into a detection model. The detection model has been trained by machine learning to output information regarding whether the subject has dysarthria by using voice information inputted.

Abstract: An articulation abnormality detection method includes: calculating an acoustic feature from utterance data of a speaker; calculating, from the acoustic feature, a first speaker feature indicating a speaker characteristic of the utterance data by using a trained deep neural network (DNN); calculating a degree of similarity between a second speaker feature of the speaker and the first speaker feature, where the second speaker feature is a speaker feature obtained when the speaker articulated properly; and determining whether the speaker has an articulation abnormality, based on the degree of similarity.