Quantifying incoherence in speech: An automated methodology and novel application to schizophrenia
Brita Elvevåg, Peter W. Foltz, Daniel R. Weinberger, and Terry E. Goldberg
Abstract
Incoherent discourse, with a disjointed flow of ideas, is a cardinal
symptom in several psychiatric and neurological conditions. However,
measuring incoherence has often been complex and subjective. We sought
to validate an objective, intrinsically reliable, computational approach
to quantifying speech incoherence. Patients with schizophrenia and
healthy control volunteers were administered a variety of language tasks.
The speech generated was transcribed and the coherence computed using
Latent Semantic Analysis (LSA). The discourse was also analyzed with a
standard clinical measure of thought disorder. In word association and
generation tasks LSA derived coherence scores were sensitive to
differences between patients and controls, and correlated with clinical
measures of thought disorder. In speech samples LSA could be used to
localize where in sentence production incoherence occurs, predict levels
of incoherence as well as whether discourse "belonged" to a
patient or control. In conclusion, LSA can be used to assay disordered
language production so as to both complement human clinical ratings as
well as experimentally parse this incoherence in a theory-driven manner.
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