Clinician vs. Machine: Estimating Vocalizations Rates in Young Children With Developmental Disorders.

Abstract

The purpose of this study was to investigate the reliability of an automated language analysis system, the Language Environment Analysis (LENA), compared with a human transcriber to determine the rate of child vocalizations during recording sessions that were significantly shorter than recommended for the automated device. Participants were 6 nonverbal male children between the ages of 28 and 46 months. Two children had autism diagnoses, 2 had Down syndrome, 1 had a chromosomal deletion, and 1 had developmental delay. Participants were recorded by the LENA digital language processor during 14 play-based interactions with a responsive adult. Rate of child vocalizations during each of the 84 recordings was determined by both a human transcriber and the LENA software. A statistically significant difference between the 2 methods was observed for 4 of the 6 participants. Effect sizes were moderate to large. Variation in syllable structure did not explain the difference between the 2 methods. Vocalization rates from the 2 methods were highly correlated for 5 of the 6 participants. Estimates of vocalization rates from nonverbal children produced by the LENA system differed from human transcription during sessions that were substantially shorter than the recommended recording length. These results confirm the recommendation of the LENA Foundation to record sessions of at least 1 hr.