Evidence map›Paper›PMID 31936586›Full record

ArticleBrain sciences2020

Infants Segment Words from Songs-An EEG Study.

Tineke M Snijders, Titia Benders, Paula Fikkert

Abstract read
In one paragraph

Article in Brain sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Melody and Lyrics Are Integrated by Late Infancy During Recognition of Music Learned at Home.Infancy : the official journal of the International Society on Infant Studies
    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

3 authors.

Tineke M SnijdersLanguage Development Department, Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands.
Titia BendersDepartment of Linguistics, Macquarie University, North Ryde NSW 2109, Australia.
Paula FikkertDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6500 HB Nijmegen, The Netherlands.

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek 275-89-023
6 · The paper itself

Abstract

Children's songs are omnipresent and highly attractive stimuli in infants' input. Previous work suggests that infants process linguistic-phonetic information from simplified sung melodies. The present study investigated whether infants learn words from ecologically valid children's songs. Testing 40 Dutch-learning 10-month-olds in a familiarization-then-test electroencephalography (EEG) paradigm, this study asked whether infants can segment repeated target words embedded in songs during familiarization and subsequently recognize those words in continuous speech in the test phase. To replicate previous speech work and compare segmentation across modalities, infants participated in both song and speech sessions. Results showed a positive event-related potential (ERP) familiarity effect to the final compared to the first target occurrences during both song and speech familiarization. No evidence was found for word recognition in the test phase following either song or speech. Comparisons across the stimuli of the present and a comparable previous study suggested that acoustic prominence and speech rate may have contributed to the polarity of the ERP familiarity effect and its absence in the test phase. Overall, the present study provides evidence that 10-month-old infants can segment words embedded in songs, and it raises questions about the acoustic and other factors that enable or hinder infant word segmentation from songs and speech.

Indexed as

EEGERPfamiliarityinfantpolarityrecognitionsongspeechword segmentation

Identifiers

PMID31936586
PMCPMC7017257

What OpenQuestion holds

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Registered trials

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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.