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Bunce, J., Soderstrom, M., Bergelson, E., Rosemberg, C., Stein, A., Alam, F., Migdalek, M. J., & Casillas, M. (2024). A cross-linguistic examination of young children’s everyday language experiences. Journal of Child Language. Advance online publication. doi:10.1017/S030500092400028X.
Abstract
We present an exploratory cross-linguistic analysis of the quantity of target-child-directed speech and adult-directed speech in North American English (US & Canadian), United Kingdom English, Argentinian Spanish, Tseltal (Tenejapa, Mayan), and Yélî Dnye (Rossel Island, Papuan), using annotations from 69 children aged 2–36 months. Using a novel methodological approach, our cross-linguistic and cross-cultural findings support prior work suggesting that target-child-directed speech quantities are stable across early development, while adult-directed speech decreases. A preponderance of speech from women was found to a similar degree across groups, with less target-child-directed speech from men and children in the North American samples than elsewhere. Consistently across groups, children also heard more adult-directed than target-child-directed speech. Finally, the numbers of talkers present in any given clip strongly impacted children’s moment-to-moment input quantities. These findings illustrate how the structure of home life impacts patterns of early language exposure across diverse developmental contexts.Additional information
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Casillas, M., Foushee, R., Méndez Girón, J., Polian, G., & Brown, P. (2024). Little evidence for a noun bias in Tseltal spontaneous speech. First Language, 44(6), 600-628. doi:10.1177/01427237231216571.
Abstract
This study examines whether children acquiring Tseltal (Mayan) demonstrate a noun bias – an overrepresentation of nouns in their early vocabularies. Nouns, specifically concrete and animate nouns, are argued to universally predominate in children’s early vocabularies because their referents are naturally available as bounded concepts to which linguistic labels can be mapped. This early advantage for noun learning has been documented using multiple methods and across a diverse collection of language populations. However, past evidence bearing on a noun bias in Tseltal learners has been mixed. Tseltal grammatical features and child–caregiver interactional patterns dampen the salience of nouns and heighten the salience of verbs, leading to the prediction of a diminished noun bias and perhaps even an early predominance of verbs. We here analyze the use of noun and verb stems in children’s spontaneous speech from egocentric daylong recordings of 29 Tseltal learners between 0;9 and 4;4. We find weak to no evidence for a noun bias using two separate analytical approaches on the same data; one analysis yields a preliminary suggestion of a flipped outcome (i.e. a verb bias). We discuss the implications of these findings for broader theories of learning bias in early lexical development. -
Lutzenberger, H., Casillas, M., Fikkert, P., Crasborn, O., & De Vos, C. (2024). More than looks: Exploring methods to test phonological discrimination in the sign language Kata Kolok. Language Learning and Development, 20(4), 297-323. doi:10.1080/15475441.2023.2277472.
Abstract
The lack of diversity in the language sciences has increasingly been criticized as it holds the potential for producing flawed theories. Research on (i) geographically diverse language communities and (ii) on sign languages is necessary to corroborate, sharpen, and extend existing theories. This study contributes a case study of adapting a well-established paradigm to study the acquisition of sign phonology in Kata Kolok, a sign language of rural Bali, Indonesia. We conducted an experiment modeled after the familiarization paradigm with child signers of Kata Kolok. Traditional analyses of looking time did not yield significant differences between signing and non-signing children. Yet, additional behavioral analyses (attention, eye contact, hand behavior) suggest that children who are signers and those who are non-signers, as well as those who are hearing and those who are deaf, interact differently with the task. This study suggests limitations of the paradigm due to the ecology of sign languages and the sociocultural characteristics of the sample, calling for a mixed-methods approach. Ultimately, this paper aims to elucidate the diversity of adaptations necessary for experimental design, procedure, and analysis, and to offer a critical reflection on the contribution of similar efforts and the diversification of the field.Additional information
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Casillas, M., Brown, P., & Levinson, S. C. (2021). Early language experience in a Papuan community. Journal of Child Language, 48(4), 792-814. doi:10.1017/S0305000920000549.
Abstract
The rate at which young children are directly spoken to varies due to many factors, including (a) caregiver ideas about children as conversational partners and (b) the organization of everyday life. Prior work suggests cross-cultural variation in rates of child-directed speech is due to the former factor, but has been fraught with confounds in comparing postindustrial and subsistence farming communities. We investigate the daylong language environments of children (0;0–3;0) on Rossel Island, Papua New Guinea, a small-scale traditional community where prior ethnographic study demonstrated contingency-seeking child interaction styles. In fact, children were infrequently directly addressed and linguistic input rate was primarily affected by situational factors, though children’s vocalization maturity showed no developmental delay. We compare the input characteristics between this community and a Tseltal Mayan one in which near-parallel methods produced comparable results, then briefly discuss the models and mechanisms for learning best supported by our findings. -
Cychosz, M., Cristia, A., Bergelson, E., Casillas, M., Baudet, G., Warlaumont, A. S., Scaff, C., Yankowitz, L., & Seidl, A. (2021). Vocal development in a large‐scale crosslinguistic corpus. Developmental Science, 24(5): e13090. doi:10.1111/desc.13090.
Abstract
This study evaluates whether early vocalizations develop in similar ways in children across diverse cultural contexts. We analyze data from daylong audio recordings of 49 children (1–36 months) from five different language/cultural backgrounds. Citizen scientists annotated these recordings to determine if child vocalizations contained canonical transitions or not (e.g., “ba” vs. “ee”). Results revealed that the proportion of clips reported to contain canonical transitions increased with age. Furthermore, this proportion exceeded 0.15 by around 7 months, replicating and extending previous findings on canonical vocalization development but using data from the natural environments of a culturally and linguistically diverse sample. This work explores how crowdsourcing can be used to annotate corpora, helping establish developmental milestones relevant to multiple languages and cultures. Lower inter‐annotator reliability on the crowdsourcing platform, relative to more traditional in‐lab expert annotators, means that a larger number of unique annotators and/or annotations are required, and that crowdsourcing may not be a suitable method for more fine‐grained annotation decisions. Audio clips used for this project are compiled into a large‐scale infant vocalization corpus that is available for other researchers to use in future work. -
Frost, R. L. A., & Casillas, M. (2021). Investigating statistical learning of nonadjacent dependencies: Running statistical learning tasks in non-WEIRD populations. In SAGE Research Methods Cases. doi:10.4135/9781529759181.
Abstract
Language acquisition is complex. However, one thing that has been suggested to help learning is the way that information is distributed throughout language; co-occurrences among particular items (e.g., syllables and words) have been shown to help learners discover the words that a language contains and figure out how those words are used. Humans’ ability to draw on this information—“statistical learning”—has been demonstrated across a broad range of studies. However, evidence from non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies is critically lacking, which limits theorizing on the universality of this skill. We extended work on statistical language learning to a new, non-WEIRD linguistic population: speakers of Yélî Dnye, who live on a remote island off mainland Papua New Guinea (Rossel Island). We performed a replication of an existing statistical learning study, training adults on an artificial language with statistically defined words, then examining what they had learnt using a two-alternative forced-choice test. Crucially, we implemented several key amendments to the original study to ensure the replication was suitable for remote field-site testing with speakers of Yélî Dnye. We made critical changes to the stimuli and materials (to test speakers of Yélî Dnye, rather than English), the instructions (we re-worked these significantly, and added practice tasks to optimize participants’ understanding), and the study format (shifting from a lab-based to a portable tablet-based setup). We discuss the requirement for acute sensitivity to linguistic, cultural, and environmental factors when adapting studies to test new populations.
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Räsänen, O., Seshadri, S., Lavechin, M., Cristia, A., & Casillas, M. (2021). ALICE: An open-source tool for automatic measurement of phoneme, syllable, and word counts from child-centered daylong recordings. Behavior Research Methods, 53, 818-835. doi:10.3758/s13428-020-01460-x.
Abstract
Recordings captured by wearable microphones are a standard method for investigating young children’s language environments. A key measure to quantify from such data is the amount of speech present in children’s home environments. To this end, the LENA recorder and software—a popular system for measuring linguistic input—estimates the number of adult words that children may hear over the course of a recording. However, word count estimation is challenging to do in a language-independent manner; the relationship between observable acoustic patterns and language-specific lexical entities is far from uniform across human languages. In this paper, we ask whether some alternative linguistic units, namely phone(me)s or syllables, could be measured instead of, or in parallel with, words in order to achieve improved cross-linguistic applicability and comparability of an automated system for measuring child language input. We discuss the advantages and disadvantages of measuring different units from theoretical and technical points of view. We also investigate the practical applicability of measuring such units using a novel system called Automatic LInguistic unit Count Estimator (ALICE) together with audio from seven child-centered daylong audio corpora from diverse cultural and linguistic environments. We show that language-independent measurement of phoneme counts is somewhat more accurate than syllables or words, but all three are highly correlated with human annotations on the same data. We share an open-source implementation of ALICE for use by the language research community, allowing automatic phoneme, syllable, and word count estimation from child-centered audio recordings.
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