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The current study aimed to identify objective acoustic measures related to affective state change in the speech of adults with post-stroke aphasia.

The speech of 20 post-stroke adults with aphasia was recorded during picture description and administration of the Western Aphasia Battery–Revised (Kertesz, 2006). In addition, participants completed the Self-Assessment Manikin (Bradley & Lang, 1994) and the Stress Scale (Tobii Dynavox, 1981–2016) before and after the language tasks. Speech from each participant was used to detect a change in affective state test scores between the beginning and ending speech.

Machine learning revealed moderate success in classifying depression, minimal success in predicting depression and stress numeric scores, and minimal success in classifying changes in affective state class between the beginning and ending speech.

The …