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

Räsänen, Okko; Seshadri, Shreyas; Karadayi, Julien; Riebling, Eric; Bunce, John; Cristià, Alejandrina; Metze, Florian; Casillas, Marisa; Rosemberg, Celia Renata; Bergelson, Elika; Söderström, Mélanie

doi:10.1016/j.specom.2019.08.005

Cited by 16 publications

(14 citation statements)

References 26 publications

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“…Data from day-long home language recordings can be processed using automated analysis software or hand coded. Limitations of automated software include variability in accuracy and precision of available tools (Räsänen et al, 2019) and lack of information on the context of recorded speech. If the recorded data are to be annotated or transcribed, an appropriate sampling procedure needs to be used as it is often not feasible to annotate the entire day-long recording (see Casillas & Cristia (2019) for a description of different sampling procedures).…”

Section: Considerations and Limitations Specific To Day-long Home Lanmentioning

confidence: 99%

The role of caregiver speech in supporting language development in infants and toddlers with autism spectrum disorder

Swanson

2020

Dev Psychopathol

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Parents play an essential role in supporting child development by providing a safe home, proper nutrition, and rich educational opportunities. In this article we focus on the role of caregiver speech in supporting development of young children with autism spectrum disorder (ASD). We review studies from typically developing children and children with autism showing that rich and responsive caregiver speech supports language development. Autism intervention studies that target caregiver speech are reviewed as are recent scientific advances from studies of typical development. The strengths and weakness of different techniques for collecting language data from caregivers and children are reviewed, and natural language samples are recommended as best practice for language research in autism. We conclude that caregivers play a powerful role in shaping their children's development and encourage researchers to adapt parent-mediated intervention studies to acknowledge individual differences in parents by using a personalized medicine approach.

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Section: Considerations and Limitations Specific To Day-long Home Lanmentioning

confidence: 99%

The role of caregiver speech in supporting language development in infants and toddlers with autism spectrum disorder

Swanson

2020

Dev Psychopathol

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“…Modern technology provides many tools for Note: the DiViMe system is no longer being actively supported, but works with some operating systems. We anticipate a newer system to emerge in the near future based on the latest developments with ALICE (Räsänen et al, 2019(Räsänen et al, , 2020.…”

Section: Concluding Thoughtsmentioning

confidence: 99%

Developing a Cross-Cultural Annotation System and MetaCorpus for Studying Infants’ Real World Language Experience

Söderström

Casillas

Bergelson

et al. 2021

Collabra: Psychology

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Recent issues around reproducibility, best practices, and cultural bias impact naturalistic observational approaches as much as experimental approaches, but there has been less focus on this area. Here, we present a new approach that leverages cross-laboratory collaborative, interdisciplinary efforts to examine important psychological questions. We illustrate this approach with a particular project that examines similarities and differences in children’s early experiences with language. This project develops a comprehensive start-to-finish analysis pipeline by developing a flexible and systematic annotation system, and implementing this system across a sampling from a “metacorpus” of audiorecordings of diverse language communities. This resource is publicly available for use, sensitive to cultural differences, and flexible to address a variety of research questions. It is also uniquely suited for use in the development of tools for automated analysis.

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“…Manually annotating many hours of everyday life is so daunting that most researchers who have recorded such data avoid it. The status quo is to declare longform manual annotation "impractical", "untenable", "not realistic", "challenging", and "unwieldy" Casillas et al, 2017;Räsänen et al, 2019;Roy et al, 2015;Tamis-LeMonda et al, 2018). Despite developmental theorists' considerable expertise in annotating behavior (Adolph, 2020;Bakeman & Gottman, 1997), scaling from researcher-constrained short activities to everyday ecologies is not straightforward.…”

Section: Quantifying Everyday Ecologies: Principles For Manual Annotation Of Many Hours Of Infants' Livesmentioning

confidence: 99%

“…Generally, it is possible to aggregate and smooth from finer-to coarser-timescales but not the reverse (Adolph, 2019). Finer-grained annotations also make for everyday datasets that are maximally useful as training and evaluation sets for developing automated algorithms to detect everyday behaviors (e.g., Räsänen et al, 2019). Theorists therefore maximize potential for insights for themselves, and for others upon sharing their annotations, by annotating the finest-grained defensible timescale (see also Principle 2).…”

Section: Principle 3: Finest-grained Defensible Timescale Of Observed Phenomena In Many Hours Of Everyday Lifementioning

confidence: 99%

Quantifying everyday ecologies: Principles for manual annotation of many hours of infants' lives

Mendoza¹,

Fausey²

2021

Preprint

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Everyday experiences are the experiences available to shape developmental change. Remarkable advances in devices used to record infants’ and toddlers’ everyday experiences, as well as in repositories to aggregate and share such recordings across teams of theorists, have yielded a potential gold mine of insights to spur next-generation theories of experience-dependent change. Making full use of these advances, however, currently requires manual annotation. Manually annotating many hours of everyday life is a dedicated pursuit requiring significant time and resources, and in many domains is an endeavor currently lacking foundational facts to guide potentially consequential implementation decisions. These realities make manual annotation a frequent ‘off ramp’ en route to discoveries, as theorists instead opt for narrower scoped activities. Here, we provide theorists with a framework for manually annotating many hours of everyday life designed to reduce both theoretical and practical overwhelm. We share insights based on our team’s recent adventures in the previously uncharted territory of everyday music. We identify principles, and share implementation examples and tools, to help theorists achieve scalable solutions to challenges that are especially fierce when annotating extended timescales. These principles for quantifying everyday ecologies will help theorists collectively maximize return on investment in databases of everyday recordings and will enable a broad community of scholars – across institutions, skillsets, experiences, and working environments – to make discoveries about the experiences upon which development may depend.

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

Cited by 16 publications

References 26 publications

The role of caregiver speech in supporting language development in infants and toddlers with autism spectrum disorder

The role of caregiver speech in supporting language development in infants and toddlers with autism spectrum disorder

Developing a Cross-Cultural Annotation System and MetaCorpus for Studying Infants’ Real World Language Experience

Quantifying everyday ecologies: Principles for manual annotation of many hours of infants' lives

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