| Literature DB >> 33936508 |
Weizhe Xu1, Jake Portanova1, Ayesha Chander2, Dror Ben-Zeev1, Trevor Cohen1.
Abstract
Thought disorder (TD) as reflected in incoherent speech is a cardinal symptom of schizophrenia and related disorders. Quantification of the degree ofTD can inform diagnosis, monitoring, and timely intervention. Consequently, there has been an interest in applying methods ofdistributional semantics to quantify incoherence ofspoken language. Prior studies have generally involved few participants and utilized speech data collected in on-site structured interviews. In this paper we conduct a comprehensive evaluation ofapproaches to quantify incoherence using distributional semantics, including a novel variant that measures the global coherence oftext. This evaluation is conducted in the context of "audio diaries" collected from participants experiencing auditory verbal hallucinations using a smartphone application. Results reveal our novel global coherence metric using the centroid (weighted vector average) outperforms established approaches in their agreement with human annotators, supporting their preferential use in the context of short recordings ofunstructured and largely spontaneous speech. ©2020 AMIA - All rights reserved.Entities:
Mesh:
Year: 2021 PMID: 33936508 PMCID: PMC8075468
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076