The Language ENvironment Analysis system (LENA): A validation study with Italian-learning children.

This study is a validation of the LENA system for the Italian language. In Study 1, to test LENA's accuracy, seventy-two 10-minute samples extracted from daylong LENA recordings were manually transcribed for 12 children longitudinally observed at 1;0 and 2;0. We found strong correlations between LENA and human estimates in the number of Adult Word Count (AWC) and Child Vocalisations Count (CVC) and a weak correlation between LENA and human estimates in Conversational Turns Count (CTC). In Study 2, to test the concurrent validity, direct and indirect language measures were considered on a sample of 54 recordings (19 children). Correlational analyses showed that LENA's CVC and CTC were significantly related to the children's vocal production, a parent report measure of prelexical vocalizations and the vocal reactivity scores. These results confirm that the automatic analyses performed by the LENA device are reliable and powerful for studying language development in Italian-speaking infants.

Is silence golden? A pilot study exploring associations between children's language environment and their language skills in Estonian-speaking families.

This two-wave longitudinal study explored how Estonian children's language environment relates to their language skills. The Language ENvironment Analysis (LENA) system's automated measures were used as a source of information about children's home language environment. Children's expressive vocabulary was measured via the parent-reported Estonian CDI III (ECDI-III), and language comprehension and production were measured via the examiner-administered New Reynell Developmental Language Scales (NRDLS). The assessments were made 1 year apart at ages 3;0 (years; months) (N = 22) and 4;0 (N = 19). The results revealed wide variability in children's home language environment and language skills. Girls' language production scores were higher; they heard a larger quantity of adult words and spent less time in noisy environments than boys at Wave 2. At Wave 1, children's word count was positively associated with productive language scores, whereas silence was negatively associated with language production and expressive vocabulary. At Wave 2, children who had been more exposed to electronic media scored higher on expressive vocabulary. Distant speech at Wave 1 was positively correlated with language comprehension scores at Wave 2 also when controlling for language comprehension scores at Wave 1. The results, which indicate that distant talk is a positive aspect and silence is a negative aspect of the language environment, highlight the importance of "languagizing" homes also in cultures where silence tends to be more highly valued and talkativeness tends to be less highly valued when compared with English-speaking middle-class families.

A thorough evaluation of the Language Environment Analysis (LENA) system.

In the previous decade, dozens of studies involving thousands of children across several research disciplines have made use of a combined daylong audio-recorder and automated algorithmic analysis called the LENAⓇ system, which aims to assess children's language environment. While the system's prevalence in the language acquisition domain is steadily growing, there are only scattered validation efforts on only some of its key characteristics. Here, we assess the LENAⓇ system's accuracy across all of its key measures: speaker classification, Child Vocalization Counts (CVC), Conversational Turn Counts (CTC), and Adult Word Counts (AWC). Our assessment is based on manual annotation of clips that have been randomly or periodically sampled out of daylong recordings, collected from (a) populations similar to the system's original training data (North American English-learning children aged 3-36 months), (b) children learning another dialect of English (UK), and (c) slightly older children growing up in a different linguistic and socio-cultural setting (Tsimane' learners in rural Bolivia). We find reasonably high accuracy in some measures (AWC, CVC), with more problematic levels of performance in others (CTC, precision of male adults and other children). Statistical analyses do not support the view that performance is worse for children who are dissimilar from the LENAⓇ original training set. Whether LENAⓇ results are accurate enough for a given research, educational, or clinical application depends largely on the specifics at hand. We therefore conclude with a set of recommendations to help researchers make this determination for their goals.

Correlation and agreement between Language ENvironment Analysis (LENA™) and manual transcription for Dutch natural language recordings.

The Language ENvironment Analysis system (LENA™) automatically analyzes the natural sound environments of children. Among other things, it estimates the amounts of adult words (AWC), child vocalizations (CV), conversational turns (CT), and electronic media (TV) that a child is exposed to. To assess LENA's reliability, we compared it to manual transcription. Specifically, we calculated the correlation and agreement between the LENA estimates and manual counts for 48 five-min audio samples. These samples were selected from eight day-long recordings of six Dutch-speaking children (ages 2-5). The correlations were strong for AWC, r = . 87, and CV, r = . 77, and comparatively low for CT, r = . 52, and TV, r = . 50. However, the agreement analysis revealed a constant bias in AWC counts, and proportional biases for CV and CT (i.e., the bias varied with the values for CV and CT). Agreement for detecting electronic media was poor. Moreover, the limits of agreement were wide for all four metrics. That is, the differences between LENA and the manual transcriptions for individual audio samples varied widely around the mean difference. This variation could indicate that LENA was affected by differences between the samples that did not equally affect the human transcribers. The disagreements and biases cast doubt on the comparability of LENA measurements across families and time, which is crucial for using LENA in research. Our sample is too small to conclude within which limits LENA's measurements are comparable, but it seems advisable to be cautious of factors that could systematically bias LENA's performance and thereby create confounds.

Reliability of the Language ENvironment Analysis system (LENA™) in European French.

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.