Alejandrina Cristia

Alejandrina Cristia is an Argentinian linguist known for research on infant-directed speech, daylong audio recordings of children's diverse linguistic environments, and language acquisition across cultures. Cristia is interested in how phonetic and phonological representations are formed during infancy and their interactions with other linguistic formats and cognitive mechanisms. She holds the position of Research Director of the Laboratoire de Sciences Cognitives et Psycholinguistique (LSCP) at the Paris Sciences et Lettres University (PSL University). She attended graduate school at Purdue University where she obtained a M.A. degree with honors in General Linguistics in 2006 and a Ph.D. degree in Linguistics in 2009 Cristia reported that language-specific factors affected infants' performance more than domain-general factors. Later, she joined the Max Planck Institute for Psycholinguistics as a scientific staff member. In 2013, Cristia became a researcher at the French National Centre for Scientific Research (CNRS) in Paris, France.

Cristia is a member of the LSCP Babylab and the Daylong recordings of Children's Language Environment (DARCLE) network. and the HomeBank Project.

Awards Cristia received Annual Prize of the Academia Argentina de Letras in 2005. In 2020, she received the CNRS Bronze medal for her research on language acquisition across cultures. and infants ability to track distributions of acoustic cues. In one of her studies with Amanda Seidl, Cristia investigated 7-month-old infants' learning of an artificial grammar, and found that infants had the ability to generate some levels of constraints and further generalize them to other related phonemes. Other research has examined the role of infant-directed speech in language development, indicating that it provides both emotional and linguistic input to assist children's language acquisition.

Besides, using randomly or periodically sampled daylong recordings, Cristia's 2020 study conducted with several other scholars across various labs evaluated the accuracy of the LENA system (a combined daylong audio-recorder and automated algorithmic analysis) in terms of the full set of its key outcome measures, namely speaker classification accuracy, child vocalization counts, conversational turn counts, and adult word counts. LENA system is known for assessing children's language environment. This study found that the LENA system is good at detecting female and the target child voices, and the system can also accurately capture the child's vocalizations while not with other talkers' vocalizations.

Selected publications

Cristia, A. (2013). Input to language: The phonetics and perception of infant-directed speech. Language and Linguistics Compass, 7(3), 157-170. Cristia, A. (2022). A systematic review suggests marked differences in the prevalence of infant-directed vocalization across groups of populations. Developmental Science, e13265. Cristia, A., Dupoux, E., Gurven, M., & Stieglitz, J. (2019). Child-directed speech is infrequent in a forager-farmer population: A time allocation study. Child Development, 90(3), 759-773. Cristia, A., Lavechin, M., Scaff, C., Soderstrom, M., Rowland, C. F., Räsänen, O., Bunce, J., & Bergelson, E. (2021). A thorough evaluation of the Language Environment Analysis (LENA) system. Behavior Research Methods, 53, 467-486. Cristia, A., & Seidl, A. (2014). The hyperarticulation hypothesis of infant-directed speech. Journal of Child Language, 41(4), 913-934. Cristia, A., & Seidl, A. (2015). Parental reports on touch screen use in early childhood. PloS one, 10(6), e0128338.