Automatic speaker diarization for natural conversation analysis in autism clinical trials.

ABSTRACT: Challenges in social communication is one of the core symptom domains in autism spectrum disorder (ASD). Novel therapies are under development to help individuals with these challenges, however the ability to show a benefit is dependent on a sensitive and reliable measure of treatment effect. Currently, measuring these deficits requires the use of time-consuming and subjective techniques. Objective measures extracted from natural conversations could be more ecologically relevant, and administered more frequently-perhaps giving them added sensitivity to change. While several studies have used automated analysis methods to study autistic speech, they require manual transcriptions. In order to bypass this time-consuming process, an automated speaker diarization algorithm must first be applied

SUBMITTER: O'Sullivan J 

PROVIDER: S-EPMC10290724 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature