Evidence map›Paper›PMID 27111272›Full record

ArticleSeminars in speech and language2016

HomeBank: An Online Repository of Daylong Child-Centered Audio Recordings.

Mark VanDam, Anne S Warlaumont, Elika Bergelson, Alejandrina Cristia, Melanie Soderstrom, Paul De Palma, Brian MacWhinney

Abstract read
In one paragraph

Article in Seminars in speech and language, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Automated Language Environment Analysis: A Research Synthesis.American journal of speech-language pathology · 2018
    Pooled it
  4. Trial
  5. Article
  6. Theoretical and Methodological Insights From Five Transcribed and Annotated Daylong Audio Recordings of Young Children's Language Environments.Perspectives on psychological science : a journal of the Association for Psychological Science · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Child and caregiver language in two different play contexts.Proceedings of the Linguistic Society of America. Linguistic Society of America. Annual Meeting · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Everyday music in infancy.Developmental science · 2021
    Article
  19. Efficient Estimation of Children's Language Exposure in Two Bilingual Communities.Journal of speech, language, and hearing research : JSLHR · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mark VanDamDepartment of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, and Spokane Hearing Oral Program of Excellence (HOPE), Spokane, Washington.
Anne S WarlaumontCognitive and Information Sciences, University of California, Merced, California.
Elika BergelsonDepartment of Brain and Cognitive Sciences, University of Rochester, Rochester, New York.
Alejandrina CristiaLaboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France.
Melanie SoderstromDepartment of Psychology, University of Manitoba, Winnipeg, MB, Canada.
Paul De PalmaDepartment of Computer Science, School of Engineering and Applied Science, Gonzaga University, Spokane, Washington.
Brian MacWhinneyDepartment of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Funding

COMPUTATIONAL ANALYSIS OF CHILD LANGUAGE TRANSCRIPT DATAR01HD023998 · NICHD · CARNEGIE-MELLON UNIVERSITY · PI MACWHINNEY, BRIAN · 1988 to 2013
$3.7M
Mechanisms of Word Learning in InfancyDP5OD019812 · OD · UNIVERSITY OF ROCHESTER · PI BERGELSON, ELIKA · 2014 to 2018
$1.9M
NICHD NIH HHS R01 HD023998NIH HHS DP5 OD019812
6 · The paper itself

Abstract

HomeBank is introduced here. It is a public, permanent, extensible, online database of daylong audio recorded in naturalistic environments. HomeBank serves two primary purposes. First, it is a repository for raw audio and associated files: one database requires special permissions, and another redacted database allows unrestricted public access. Associated files include metadata such as participant demographics and clinical diagnostics, automated annotations, and human-generated transcriptions and annotations. Many recordings use the child-perspective LENA recorders (LENA Research Foundation, Boulder, Colorado, United States), but various recordings and metadata can be accommodated. The HomeBank database can have both vetted and unvetted recordings, with different levels of accessibility. Additionally, HomeBank is an open repository for processing and analysis tools for HomeBank or similar data sets. HomeBank is flexible for users and contributors, making primary data available to researchers, especially those in child development, linguistics, and audio engineering. HomeBank facilitates researchers' access to large-scale data and tools, linking the acoustic, auditory, and linguistic characteristics of children's environments with a variety of variables including socioeconomic status, family characteristics, language trajectories, and disorders. Automated processing applied to daylong home audio recordings is now becoming widely used in early intervention initiatives, helping parents to provide richer speech input to at-risk children.

Indexed as

Databases, FactualLanguage DevelopmentLanguage DisordersVideo RecordingChildHumansLanguageParentsSpeech

Identifiers

PMID27111272
PMCPMC5570530

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.