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-tonoise 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 . Child vocalization count . Reliability . Human transcriber . European French . Automatic speech recognition technology . Signal-to-noise ratio Studies in child language acquisition and disorders generally require reliable audio recordings. Most of the time, these recordings are limited in duration since they must meet physical constraints. The main goal of the experimenter is to develop a data acquisition system that is non-invasive and also preserves the quality of the recordings. Whereas fixed recording systems can restrict the child's movements, mobile systems, usually placed on the child, may affect the quality of recordings by adding friction noises. Experimenters, as a result, have to rely upon their own ingenuity to acquire a sufficient amount of high-quality data. Still, the problems do not end there. Once the data collection stage has been completed, data processing remains a time-consuming and tedious task, even when performing simple word counts. Localization of the child's productions, versus those addressed by adults to the child, is mandatory before transcribing them and then analyzing their content. All these constraints are liable to limit the number of tested subjects, and hence the amount of data collected. To overcome these drawbacks, a system was launched in 2004 allowing for large-scale all-day audio recording and
