Automated extraction of information from Language ENvironment Analysis (LENA) home recordings of older children with autism

It has been established that children and adolescents with Autism Spectrum Disorder show a wide range of abilities to use spoken words and establish interactive conversations. Automatic measurement of such abilities in naturalistic environments would greatly facilitate assessment and monitoring of such individuals. If sufficient accuracy could be achieved, studies could be performed whose sample sizes are large enough to draw meaningful conclusions. In the current study, 16-hour home audio recordings using the LENA (Language ENvironment Analysis) device are examined for older children and adolescents. Specific enhancements to the existing LENA analysis platform include the ability to diarize recordings for subjects aged 5 through 13, to detect non-verbal vocalizations such as laughter and whining, to identify child-directed speech, and to determine when questions are posed. Other higher-level descriptors involve extraction of affect, computation of conversational interaction measures, detection of cross-t...