Okko Räsänen

Biographic Data

ID6222713
NAMEOkko Räsänen
GIVEN NAMESOkko
FAMILY NAMERäsänen
SIGNATURERASANEN O
AFFILIATIONSTampere University
ORCID0000-0002-0537-0946
VERIFIEDYes
TOTAL WORKS10
TOTAL CITATIONS0
WORKS AS AUTHOR10
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Simulating prenatal language exposure in computational models

    Open AccessMaría Andrea Cruz Blandón, Nayeli Gonzalez‐Gomez et al.ARTICLECognition2025

    Researchers have hypothesized that infant language learning starts from the third trimester of pregnancy. This is supported by studies with fetuses and newborns showing discrimination/preference for their native language. Jointly with empirical research, initial computational modeling studies have investigated whether learning language patterns from speech input benefits from auditory prenatal language exposure (PLE), showing some advantages for …

  • Motherese Directed at Prelinguistic Infants at Risk for Neurological Disorders

    Open AccessOkko Räsänen, Manu Airaksinen et al.ARTICLEJournal of Child Language2025

    To investigate how a high risk for infant neurological impairment affects the quality of infant verbal interactions, and in particular properties of infant-directed speech, spontaneous interactions between 14 mothers and their 4.5-month-old infants at high risk for neurological disorders (7 female) were recorded and acoustically compared with those of 14 dyads with typically developing infants (8 female). Mothers of at-risk infants had proportion…

  • The difficulty and importance of estimating the lower and upper bounds of infant speech exposure

    Joseph R Coffey, Okko Räsänen et al.PREPRINT2024

    Estimates of infants’ language exposure are necessary for computational studies that attempt to model and learn from infant language experiences. However, there are no well-established input estimates usable for this purpose. This paper explores empirical data on infant language exposure across various cultural settings to derive plausible limits on the speech exposure infants might receive during their first years of life. First, we argue that s…

  • Establishing the reliability of metrics extracted from long-form recordings using Lena and the Aclew pipeline

    Open AccessAlejandrina Cristia, Lucas Gautheron et al.ARTICLEBehavior Research Methods2024

    Long-form audio recordings are increasingly used to study individual variation, group differences, and many other topics in theoretical and applied fields of developmental science, particularly for the description of children's language input (typically speech from adults) and children's language output (ranging from babble to sentences). The proprietary LENA software has been available for over a decade, and with it, users have come to rely on d…

  • Introducing meta-analysis in the evaluation of computational models of infant language development

    María Andrea Cruz Blandón, Alejandrina Cristia et al.PREPRINT2021

    Computational models of child language development can help us understand the cognitive underpinnings of the language learning process, which occurs along several linguistic levels at once (e.g., prosodic and phonological). However, in light of the replication crisis, modellers face the challenge of selecting representative and consolidated infant data. Thus, it is desirable to have evaluation methodologies that could account for robust empirical…

  • Alice

    Okko Räsänen, Shreyas Seshadri et al.PREPRINT2020

    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 cha…

  • Alice

    Open AccessOkko Räsänen, Shreyas Seshadri et al.ARTICLEBehavior Research Methods2020

    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 cha…

  • A thorough evaluation of the Language Environment Analysis (Lena) system

    Open AccessAlejandrina Cristia, Marvin Lavechin et al.ARTICLEBehavior Research Methods2020

  • Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech

    Okko Räsänen, Shreyas Seshadri et al.PREPRINT2019

    Automatic word count estimation (WCE) from audio recordings can be used to quantify the amount of verbal communication in a recording environment. One key application of WCE is to measure language input heard by infants and toddlers in their natural environments, as captured by daylong recordings from microphones worn by the infants. Although WCE is nearly trivial for high-quality signals in high-resource languages, daylong recordings are substan…

  • A thorough evaluation of the Language Environment Analysis (Lenatm) system

    Alejandrina Cristia, Marvin Lavechin et al.PREPRINT2019

    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. H…