Children's early language development has always been a challenge to measure. So, therapists have historically relied on their trained ears and the use of paper-based assessments. A recent technological advance may hold the key to future language assessment. A group of researchers from the U.S. and Austria has been using an all-day recording device (see image above) to make naturalistic recordings of children's vocalizations. They have been recording and analyzing syllable patterns and found that they can reliably distinguish groups of children with autism, children with language delay and typically developing children.
The device itself weighs about one eighth of a pound, can be worn on the child's clothing and makes recordings of the child's natural speech across a whole day. The data the study team collected included 1,486 all-day recordings, from 232 children with more than 3.1 million child vocalizations. The rhythm of the vocalization and the pattern of syllables were analyzed. The study team looked at whether the vocal patterns predicted later language development and also whether the speech pattern could reliably differentiate the three different groups of children.
Vocalization patterns of children with autism were characteristically different from those of typically developing children, and to a lesser degree the analysis also differentiated children with autism from children with language delay. The characteristic that most reliably differentiated the groups was the ability to break down the vocalization into syllables. The ability to form syllables was a significant predictor of future language development.
This technology offers an exciting opportunity to identify children whose language development may be atypical and could be at risk for autism. If further independent studies demonstrate its efficacy, the portability of this technology and its relative ease of use may offer another helpful screening tool for autism. This technology also has potential to be used alongside traditional methods of screening and diagnosing children with autism to increase the reliability of diagnostic assessments. Therapists may use this information to augment their current clinical practice and knowledge and assist them in monitoring a child's everyday vocalizations in natural settings. It will also help therapists predict children's later language development which can inform the type and timing of interventions.