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Am J Speech Lang Pathol May 2017 PMID 28418456

Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis.

Jill Gilkerson, Jeffrey A Richards, Steven F Warren, Judith K Montgomery, Charles R Greenwood, D Kimbrough Oller, John H L Hansen, Terrance D Paul

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Mentions

130
Peak: 4 in Jul 2020
across 5 sources since Feb 2019

Extended reach

199,378
potential audience

Total likes

63

Video views

167

Mentions per month

Feb 2019 – Oct 2025

Where it's discussed

  • News99 articles
  • X / Twitter21 posts
  • Blogs6 articles
  • YouTube2 videos
  • Facebook2 posts

AI synopsis

What people are saying

The collection of discussions reflects a balanced view, with some participants noting replication efforts and possible biases, such as mentions of the 'word gap' being closer to 4 million words and concerns about racial bias, showing critical thinking about both the methodological and societal implications of the research. The tone varies from technical analysis to curiosity about the findings' real-world significance.

AgreementNeither agree nor disagree

The discussions show mixed opinions; some acknowledge the study's validity, while others point out issues like variability and replication concerns.

InterestModerate interest

Participants are somewhat interested, with several referencing the potential implications and replication efforts, but overall curiosity remains moderate.

EngagementModerate engagement

Comments include technical details, references to related studies, and debates about methodology, indicating some level of thoughtful engagement.

ImpactModerate impact

The discussions highlight the importance of the research, especially in the context of developmental and linguistic assessments, suggesting a modest perceived impact.

Abstract in brief

  • This research used automated recordings and analysis to create a standardized way to measure early language environments in children from ages 2 to 48 months, comparing these measures to traditional language assessments and socioeconomic factors.
  • Children’s vocalizations and conversational exchanges increased with age, while adult word exposure remained steady after infancy; children from lower socioeconomic backgrounds had fewer vocalizations, interactions, and words, though there was high variability within groups.
  • The findings provide new insights into early language environments and have potential clinical uses for identifying children at risk of poor language development due to limited language exposure.
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Top posts

Most liked on X and Bluesky
Delip Rao e/σ
@deliprao · X

GPT-3 is trained on 200 billion words. An average 13 year old sees at most a 100 million words in their lifetime. So for every word this teenager sees, GPT3 has seen over 2000 words! https://t.co/RFYvPVUGCt

Dec 28, 2022 · 40 likes · 63,069 followers View post →
ASHA Journals
@ASHAJournals · X

(9 of 11) One of our MOST SHARED ARTICLES OF 2018! Mapping the Early #Language Environment Using All-Day Recordings & Automated Analysis https://t.co/ybOWInXB5L @LENAEarlyTalk @kulifespan @uofmemphis @UT_Dallas @DKimbroughOller #AJSLP #ASHAJournals @SIGPerspectives https://t.co/MR6WJA1kP2

Mar 3, 2019 · 6 likes · 1 share · 17,020 followers View post →
Ian Cushing
@ian_cushing · X

@EALDominicB https://t.co/tXCvonNjaV

Jun 29, 2022 · 4 likes · 11,169 followers View post →
エミリー
@emily_luvcat · X

⤴️の2017年の研究はこれね。 https://t.co/zxZi0Inspu

Oct 31, 2025 · 3 likes · 21,708 followers View post →
Colegio Logopedas PV
@LogPv · X

Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. https://t.co/Fk4AZq9TAn

Jul 22, 2020 · 3 likes · 2 shares · 1,504 followers View post →
Ian Cushing
@ian_cushing · X

@jnyrose https://t.co/tXCvonNjaV

Jun 29, 2022 · 2 likes · 11,169 followers View post →

All mentions

エミリー
@emily_luvcat · X

⤴️の2017年の研究はこれね。 https://t.co/zxZi0Inspu

Oct 31, 2025 · 3 likes · 21,708 followers View post →
Sarah
@4whossayingwhat · X

@kapelianis @HeathMayo This was covered in one of my ECE classes. The original study has some issues but got the fundamentals right. https://t.co/XZjgtwFK2E https://t.co/pQMAlZInrr https://t.co/Mal1F4lHou

Jul 6, 2023 · 21 followers View post →
George
@gorge_lilley · X

@TERPodcast 3/ Another much larger study concluded the gap was about 4 million - https://t.co/vSCBo1h9mM

Jan 4, 2023 · 1 like · 360 followers View post →
Delip Rao e/σ
@deliprao · X

GPT-3 is trained on 200 billion words. An average 13 year old sees at most a 100 million words in their lifetime. So for every word this teenager sees, GPT3 has seen over 2000 words! https://t.co/RFYvPVUGCt

Dec 28, 2022 · 40 likes · 63,069 followers View post →
Alex Warstadt
@a_stadt · X

@symbolicstorage It's really an order or magnitude estimate. Hart & Risley (1993) say 10M words per year is on the upper end. Gilkerson et al's (2017) much better data extrapolates to about 3-6M words per year. https://t.co/GZCeQG3z17

Aug 22, 2022 · 1 like · 1,817 followers View post →
Ian Cushing
@ian_cushing · X

@EALDominicB https://t.co/tXCvonNjaV

Jun 29, 2022 · 4 likes · 11,169 followers View post →
Ian Cushing
@ian_cushing · X

@jnyrose https://t.co/tXCvonNjaV

Jun 29, 2022 · 2 likes · 11,169 followers View post →
Matthias Prohl
@ma_promat · X

@R3gretting @titiatscriptor Das Experiment ist 2014-16 methodisch sauberer wiederholt worden. Ergebnisse waren im Kern gleich - wichtig war jedoch die hohe Varianz innerhalb der Gruppen. Es reicht nicht den Brockhaus vom Band abzuspielen, sondern es geht um die aktive Interaktion. https://t.co/gie0oUjYZ8 https://t.co/I29tjiTYVc

Aug 25, 2021 · 399 followers View post →
Jim Bloom
@jimmyroybloom · X

https://t.co/pg1sZqgJvx

Oct 7, 2020 · 2,472 followers View post →
tatiana_almeida
@rouge_tatiana · X

RT @LogPv: Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. https://t.co/Fk4AZq9TAn

Jul 23, 2020 · 2 shares · 337 followers View post →
ColeLogopedasMadrid
@ColeLogoMadrid · X

RT @LogPv: Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. https://t.co/Fk4AZq9TAn

Jul 23, 2020 · 2 shares · 2,292 followers View post →
Colegio Logopedas PV
@LogPv · X

Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis. https://t.co/Fk4AZq9TAn

Jul 22, 2020 · 3 likes · 2 shares · 1,504 followers View post →
Matt Krause
@prokraustinator · X

@DavidPetrus94 (Data from Gilkerson et al., 2017): https://t.co/70cuJKF03J)

Jul 20, 2020 · 1,069 followers View post →
Linguistics Girl MLS MS
@LinguisticsGirl · X

A recent replication of the "30 million word gap" study found the "word gap" may be closer to 4 million words. That's quite a difference. Not to mention the racial bias in the original study, among other criticisms. https://t.co/Iix7YFQuFy https://t.co/sPtqISRg59 https://t.co/JiKY4Z1PBI

Mar 9, 2020 · 1 like · 5,446 followers View post →
Alphonse
@corasundae · X

@amyvaz3 It's not unique words, it is in the millions (4 million), and it has been replicated with a larger sample. https://t.co/0IREthhOKA

Sep 16, 2019 · 440 followers View post →
Alphonse
@corasundae · X

@Aldowyn @eveewing @JessicaCalarco https://t.co/0IREthhOKA It's been replicated though?

Sep 16, 2019 · 440 followers View post →
Alphonse
@corasundae · X

@jaybeware https://t.co/s8CbC6rHvE https://t.co/0IREthhOKA He's citing this study, not that one.

Sep 16, 2019 · 440 followers View post →
Sharon Vince
@SharonMarie80 · X

@etaknipsa https://t.co/bhumfnYXH6

Jun 25, 2019 · 1 like · 1,096 followers View post →
ASHA Journals
@ASHAJournals · X

(9 of 11) One of our MOST SHARED ARTICLES OF 2018! Mapping the Early #Language Environment Using All-Day Recordings & Automated Analysis https://t.co/ybOWInXB5L @LENAEarlyTalk @kulifespan @uofmemphis @UT_Dallas @DKimbroughOller #AJSLP #ASHAJournals @SIGPerspectives https://t.co/MR6WJA1kP2

Mar 3, 2019 · 6 likes · 1 share · 17,020 followers View post →
CLaE
@leafs_s · X

RT @leafs_s: American Journal of Speech-Language Pathology 17 May 2017 Mapping the Early Language Environment Using All-Day Recordings and…

Feb 19, 2019 · 1 share · 28,463 followers View post →
CLaE
@leafs_s · X

American Journal of Speech-Language Pathology 17 May 2017 Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis https://t.co/ReyfnamjBd

Feb 19, 2019 · 1 like · 1 share · 28,463 followers View post →