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[See full abstract in the pdf] Formal Thought Disorder (FTD), which is agroup of symptoms in cognition that affects language and thought, can beobserved through language. FTD is seen across such developmental or psychiatricdisorders as Autism Spectrum Disorder (ASD) or Schizophrenia, and its relatedSchizotypal Personality Disorder (SPD). This paper collected a Japaneseaudio-report dataset with score labels related to ASD and SPD through acrowd-sourcing service from the general population. We measured languagecharacteristics with the 2nd edition of the Social Responsiveness Scale (SRS2)and the Schizotypal Personality Questionnaire (SPQ), including an odd speechsubscale from SPQ to quantify the FTD symptoms. We investigated the followingfour research questions through machine-learning-based score predictions: (RQ1)How are schizotypal and autistic measures correlated? (RQ2) What is the mostsuitable task to elicit FTD symptoms? (RQ3) Does the length of speech affectthe elicitation of FTD symptoms? (RQ4) Which features are critical forcapturing FTD symptoms? We confirmed that an FTD-related subscale, odd speech,was significantly correlated with both the total SPQ and SRS scores, althoughthey themselves were not correlated significantly. Our regression analysisindicated that longer speech about a negative memory elicited more FTDsymptoms. The ablation study confirmed the importance of function words andboth the abstract and temporal features for FTD-related odd speech estimation.In contrast, content words were effective only in the SRS predictions, andcontent words were effective only in the SPQ predictions, a result that impliesthe differences between SPD-like and ASD-like symptoms. Data and programs usedin this paper can be found here:https://sites.google.com/view/sagatake/resource.

Computational analyses of linguistic features with schizophrenic and autistic traits along with formal thought disorders