Daily auditory environments in F rench-speaking infants: A longitudinal dataset (2024)

Abstract: Babies’ daily auditory environment plays a crucial role in language development. Most previous research estimating the quantitative and qualitative aspects of early speech inputs has predominantly focused on English- and Spanish-speaking families. In addition, validation studies for daylong recordings’ analysis tools are scarce on French data sets.In this paper, we present a French corpus of daylong audio recordings longitudinally collected with the LENA (Language ENvironment Analysis) system from infants aged 3 to 24 months. We conduct a thorough exploration of this data set, which serves as a quality check for both the data and the analysis tools.We evaluate the reliability of LENA metrics by systematically comparing them with those obtained from the ChildProject set of tools and by checking the known dynamics of the metrics with age. These metrics are also used to replicate, on our data set, findings from (Warlaumont et al, 2014) about the increase of infants’ speech vocalizations and temporal contingencies between infants and caregivers with age.

## introduction infants rely on their daily auditory environment to develop language and other cognitive skills. pioneering studies interested in these early auditory inputs used observatory experiments in laboratory settings or short recordings that were manually annotated @xcite . in the last decades, technological advances brought new tools that allowed the collection and analysis of more considerable and ecological datasets. daylong recordings are now increasingly used in developmental studies @xcite , especially since the release of the language environment analysis (lena) system in 2004. daily auditory environments have been described in a variety of populations @xcite @xcite , highlighting the positive effects of early caregiver-infant interactions on language development @xcite @xcite . nonetheless, only two datasets were collected in french-speaking households @xcite . here, we expand the literature by describing an original dataset of infants' daylong audio recordings gathered in twenty french-speaking families. we focused on 3-to-24-month-old babies for several reasons: (1) it allows a direct comparison with @xcite 's and @xcite results ; (2) it includes crucial steps for language development, including the emergence of phonemic categories between 6 and 10 months @xcite , and the vocabulary spurt between 18 and 24 months @xcite @xcite ; (3) the two first years of life constitute a critical period where caregiver-infant interactions are early precursors of later language outcomes and cognitive skills @xcite @xcite . lena's output correlation with human annotations has been assessed in several languages, suggesting good reliability @xcite @xcite @xcite . however, only one study provided evidence for lena system reliability in european french, yielding relatively good results @xcite . moreover, lena validation studies implied listening to the continuous raw audio recordings. in addition to being highly time-consuming, this approach raises critical ethical issues associated with data privacy @xcite . here, we override these difficulties by comparing the lena metrics outputs with other annotation systems. the paper has the following contributions: (i) describe a new french corpus of auditory lenarecorded data, (ii) compare different automatic annotation tools, (iii) provide a picture of the daily auditory environment in french-speaking families in 3-to-24-months infants, (iv) show the potential of the data set by replicating daylong recordingsbased results on developmental trajectories. ## related work this section is a brief overview of the existing literature regarding daylong recording studies in developmental populations. we identified two main types of studies: (i) experimental studies that used daylong recordings as a tool to answer a specific research question and (ii) validation studies that focused on assessing the reliability of the recording and analysis tools themselves. ## tools and methods daylong recordings present a set of challenges in terms of processing. the first constraint is the data set size: we gathered 10 4 hours of highly heterogeneous recordings (both across and within recordings) that need to be sampled. existing literature has used the notion of hot spots (areas in the recordings with a high density of speech events) as well as a method consisting of human labeling of extremely short sound events @xcite . due to the required infrastructure, the latter approach was not considered for our work. instead, we applied state-of-the-art computational techniques and packages to perform step-by-step reliability tests and calculate agreement scores between them. the automatic tools we used for our analyses are the lena suite @xcite and a set of tools developed or adapted whithin the framework of childproject @xcite . ## data set the corpus currently consists of 8286 hours of lena daylong recordings. ## discussion the collection and investigation of our original corpus in french households facilitated the comparison of different analysis tools and the replication of previous results within the same age ranges. first, we identified a robust relationship between target child production metrics and age. as expected, we did not observe a similar significant 2 following @xcite and @xcite , who followed oller et al. @xcite , which used a 1second window to extract relevant vocal activity to investigate the "social feedback loop" for children between 8 to 48 months. furthermore, our more detailed analysis (depicted in figure 3 ) and the replication of warlaumont's first results, showed that the increase in child's productions with age was due to speechrelated productions and not to vegetative sounds or noise. in summary, our data show that children do produce more speech while growing up in their first two years of life. these increased productions are temporally contingent on other speakers, regardless of the initiator of the interaction (target child or other speaker). this is further elaborated by the replication of warlaumont's third result about the social loop that showed the benefit of follow-up productions of adult feedback on children's speech. contrary to @xcite (but in line with @xcite we did not find any effect of parental ses, gender, or linguistic environment on children's productions. this was the same for temporal contingencies used as a proxy for measuring linguistic interaction with the child. other studies have attempted to dive further into linguistic metrics from large child-caregiver datasets. some refined the speech contingencies to distinguish corrective feedback or to approach the grammaticality evaluation of the productions in these datasets @xcite . however, those datasets have been manually transcribed, while ours did not (and will not) receive such a transcription. a second major difference is the age range of the children. most of the existing studies involved children from 12-24 months up to later ages. this inevitably changes the nature and characteristics of the metrics that can be extracted. another trend of work focuses on phonetic learning based on daylong recordings, such as lavechin et al. (2024) on perceptual attunement. finally, in a more cultural and typological direction, bergelson et al. (2023) studied a global sample of 1,001 childcentered audio capturing 2-to 48-months-olds from many countries and various cultural backgrounds. ## conclusion this work first constitutes a replication of earlier results on daylong recordings, on a completely new and independent data set, using two different tools. this contributes to answer cruz blandón et al. (2023)'s call for more and better meta-studies on long recordings. indeed, despite their creation cost, daylong recordings' significance is growing in cognitive science. showing that these data sets, despite their noisy nature, do present enough reliability to gain insights about the children's language and communicative skills development is crucial. the second contribution consists of the characterization of our data set itself. it is a large data set (>8000 hours of recordings) that is still growing at the time of writing. it is unique by being truly longitudinal with some children's environments being recorded over a two-year span. finally, other experimental data were collected longitudinally in the same sample of infants. these are beyond the scope of this paper but open up the possibilities of cross-analyses between the characterization of the linguistic environment and other experimental results regarding language development. the present study, therefore, constitutes a crucial first step in this direction through the thorough exploration of the data set, and by considering individual variability. from here, we now plan to refine the analyses by entering into more linguistic characterizations of these productions in terms of richness. we will consider tools that allow for more phonological measures such as @xcite and more content-based metrics @xcite ) that have been used so far only on transcript-based corpora from childes @xcite and that can be now explored on daylong recordings thanks to the improvement of automatic speech recognition engines.