Automatic analysis of LENA recordings for language assessment in children aged five to fourteen years with application to individuals with autism

Detecting child and adult vocalizations, and computing their characteristics from audio recorded in natural home environments can be useful in many applications. The current study is interested in monitoring children with autism spectrum disorder to ultimately provide outcome measures that can track the efficacy of clinical treatments. In this paper, we show that it is possible to automate detection of child and adult vocalizations from audio recorded in controlled clinic environments as well as in naturalistic home settings. The results show both high precision and recall for children aged five to fourteen years who have been diagnosed with autism. Further, we describe a highly accurate speaker-independent laughter detector for this age group which will be useful for affect estimation.