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Quantity Meets Quality: Examining input statistics for early word learning from the infant’s point of view

Award Number: R01HD119490
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/06/2025
PERIOD OF PERFORMANCE END DATE: 05/31/2030

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Quantity Meets Quality: Examining input statistics for early word learning from the infant’s point of view - Quantity Meets Quality: Examining input statistics for early word learning from the infant's point of view Project Summary / Abstract Children acquire language in everyday contexts where the language environment plays a critical role in supporting early language development. In early word learning, infants learn object names by linking heard words to seen objects in their environment. This is well recognized as a computationally complex problem due to referential uncertainty -- at the moment of hearing any word, there may be many potential referents in the learner's immediate environment. Many laboratory experiments are designed based on various assumptions about the uncertainty challenge that young learners face, which may not reflect the uncertainty encountered in everyday learning experiences. Despite considerable research efforts, little is known about the referential uncertainty infants face in their everyday contexts. We built a Home-like Observational Multimodal Environment (HOME) to examine how 12- to 24-month-olds and their parents jointly create input statistics for early word learning in everyday activities. Using head-mounted eye-tracking technology in the HOME lab, we will record infant gaze and parent speech during three everyday activities: toy play, book reading, and meal preparation. We will specifically focus on the moments when parents produce object names in their speech, precisely measuring the infants' in-the- moment attention toward those named objects. Through the analyses of high-density gaze and speech data, we will characterize the referential uncertainty at individual naming instances from the infant's point of view (Aim 1), examine the computational mechanisms that operate on the input statistics to achieve successful word learning (Aim 2), compare the quantity and quality of the input statistics among the three different everyday activities (Aim 3), and determine whether the quantity and quality of the input statistics in those activities predict individual differences in vocabulary growth (Aim 4). This proposed work holds significant potential for breaking barriers that stall the current understanding of early word learning, developing innovative methods to quantify the multimodal nature of the language environment, and providing mechanistic insights into the origins and consequences of individual differences in language development.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $331,729 )
2026	2026	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Child Health and Human Development Extramural Research	000	2	5/11/2026	NON-COMPETING CONTINUATION	$331,729
														Subtotal = $331,729

Issue Date FY: 2025 ( Subtotal = $344,356 )
2025	2025	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Child Health and Human Development Extramural Research	000	1	9/6/2025	NEW	$344,356
														Subtotal = $344,356

Grand Total All Awards = $676,085

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Quantity Meets Quality: Examining input statistics for early word learning from the infant’s point of view

Award Number: R01HD119490

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/06/2025

PERIOD OF PERFORMANCE END DATE: 05/31/2030

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