In this study, we examined the accuracy of the Language ENvironment Analysis (LENA) system in European French. LENA is a digital recording device with software that facilitates the collection and analysis of audio recordings from young children, providing automated measures of the speech overheard and produced by the child. Eighteen native French-speaking children, who were divided into six age groups ranging from 3 to 48 months old, were recorded about 10-16 h per day, three days a week. A total of 324 samples (six 10-min chunks of recordings) were selected and then transcribed according to the CHAT format. Simple and mixed linear models between the LENA and human adult word count (AWC) and child vocalization count (CVC) estimates were performed, to determine to what extent the automatic and the human methods agreed. Both the AWC and CVC estimates were very reliable (r = .64 and .71, respectively) for the 324 samples. When controlling the random factors of participants and recordings, 1 h was sufficient to obtain a reliable sample. It was, however, found that two age groups (7-12 months and 13-18 months) had a significant effect on the AWC data and that the second day of recording had a significant effect on the CVC data. When noise-related factors were added to the model, only a significant effect of signal-to-noise ratio was found on the AWC data. All of these findings and their clinical implications are discussed, providing strong support for the reliability of LENA in French.
Keywords: Adult word count; Automatic speech recognition technology; Child vocalization count; European French; Human transcriber; Reliability; Signal-to-noise ratio.