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Computerized analysis of speech and language to identify psycholinguistic correlates of frontotemporal lobar
Serguei V S Pakhomov1, Glenn E Smith, Dustin Chacon
1University of Minnesota, Twin Cities, MN, USA. pakh0002@umn.edu
Objective:
To evaluate the use of a semiautomated computerized system for measuring speech and language characteristics in patients with frontotemporal lobar degeneration (FTLD).
Background:
FTLD is a heterogeneous disorder comprising at least 3 variants. Computerized assessment of spontaneous verbal descriptions by patients with FTLD offers a detailed and reproducible view of the underlying cognitive deficits.
Methods:
Audiorecorded speech samples of 38 patients from 3 participating medical centers were elicited using the Cookie Theft stimulus. Each patient underwent a battery of neuropsychologic tests. The audio was analyzed by the computerized system to measure 15 speech and language variables. Analysis of variance was used to identify characteristics with significant differences in means between FTLD variants. Factor analysis was used to examine the implicit relations between subsets of the variables.
Results:
Semiautomated measurements of pause-to-word ratio and pronoun-to-noun ratio were able to discriminate between some of the FTLD variants. Principal component analysis of all 14 variables suggested 4 subjectively defined components (length, hesitancy, empty content, grammaticality) corresponding to the phenomenology of FTLD variants.
Conclusion:
Semiautomated language and speech analysis is a promising novel approach to neuropsychologic assessment that offers a valuable contribution to the toolbox of researchers in dementia and other neurodegenerative disorders.
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