Abstract
INTRODUCTION: Neurodegenerative diseases, especially frontotemporal lobar degeneration and Alzheimer's disease, often lead to impaired language functions, and so speech analysis can provide objective measures with which to classify the different syndromes. AIM: To study the nature, cognitive correlates and clinical utility of 21 variables related to speech and silence times. SUBJECTS AND METHODS: Derivation of acoustic variables with Praat in three spontaneous speech tasks conducted in 22 subjects, distributed in six diagnostic groups (five with neurodegenerative diseases + control). A descriptive analysis is performed, with ROC and principal component curves, to study how acoustic variables are related to the different neurodegenerative syndromes and what information they can provide. RESULTS: Three groups of variables are identified related, respectively, to: a) total number of silent pauses and total duration of the task; b) variability of the phonic groups; and c) variability of the periods of silence. These components correlate differentially with the different syndromes studied. CONCLUSIONS: Detailed analysis of speech and silence times can provide relevant information for the diagnosis of different neurodegenerative syndromes that are not reflected in traditional neuropsychological assessments. Thus, the total number of silent pauses may be a valuable aid in discriminating patients with lexical access deficits, phonic group parameters seem to reflect motor speech problems, and pause variability is associated with dysexecutive and global impairment.