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Vocal development in a large‐scale crosslinguistic corpus
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In: ISSN: 1363-755X ; EISSN: 1467-7687 ; Developmental Science ; https://hal.archives-ouvertes.fr/hal-03498978 ; Developmental Science, Wiley, 2021, 24 (5), ⟨10.1111/desc.13090⟩ (2021)
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Describing Vocalizations in Young Children: A Big Data Approach Through Citizen Science Annotation
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In: ISSN: 1092-4388 ; EISSN: 1558-9102 ; Journal of Speech, Language, and Hearing Research ; https://hal.archives-ouvertes.fr/hal-03498946 ; Journal of Speech, Language, and Hearing Research, American Speech-Language-Hearing Association, 2021, 64 (7), pp.2401-2416. ⟨10.1044/2021_JSLHR-20-00661⟩ (2021)
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Vocal development in a large-scale crosslinguistic corpus.
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Cychosz, Margaret; Scaff, Camila; Warlaumont, Anne S; Casillas, Marisa; Seidl, Amanda; Bergelson, Elika; Baudet, Gladys; Cristia, Alejandrina; Yankowitz, Lisa. - : Wiley, 2021
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Abstract:
This study evaluates whether early vocalizations develop in similar ways in children across diverse cultural contexts. We analyze data from daylong audio recordings of 49 children (1-36 months) from five different language/cultural backgrounds. Citizen scientists annotated these recordings to determine if child vocalizations contained canonical transitions or not (e.g., "ba" versus "ee"). Results revealed that the proportion of clips reported to contain canonical transitions increased with age. Further, this proportion exceeded 0.15 by around 7 months, replicating and extending previous findings on canonical vocalization development but using data from the natural environments of a culturally and linguistically diverse sample. This work explores how crowdsourcing can be used to annotate corpora, helping establish developmental milestones relevant to multiple languages and cultures. Lower inter-annotator reliability on the crowdsourcing platform, relative to more traditional in-lab expert annotators, means that a larger number of unique annotators and/or annotations are required and that crowdsourcing may not be a suitable method for more fine-grained annotation decisions. Audio clips used for this project are compiled into a large-scale infant vocalization corpus that is available for other researchers to use in future work.
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Keyword:
babbling; crosslinguistic; crowdsourcing; infants; naturalistic recording; speech; vocal development
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URL: https://hdl.handle.net/10161/22274
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Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference
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Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference
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In: ISSN: 2515-2459 ; EISSN: 2515-2467 ; Advances in Methods and Practices in Psychological Science ; https://hal-univ-rennes1.archives-ouvertes.fr/hal-02509817 ; Advances in Methods and Practices in Psychological Science, [Thousand Oaks]: [SAGE Publications], 2020, 3 (1), pp.24-52. ⟨10.1177/2515245919900809⟩ (2020)
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What Do North American Babies Hear? A large-scale cross-corpus analysis.
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BabbleCor: A Crosslinguistic Corpus of Babble Development in Five Languages ...
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The INTERSPEECH 2019 computational paralinguistics challenge: Styrian dialects, continuous sleepiness, baby sounds & orca activity
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Vocal and Tactile Input to Children Who Are Deaf or Hard of Hearing
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In: J Speech Lang Hear Res (2019)
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English-learning infants’ perception of word stress patterns
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The impact of brief restriction to articulation on children's subsequent speech production
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Touch Screen Assessment of At-risk Infant Comprehension
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In: Theses and Dissertations Available from ProQuest (2018)
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What Do North American Babies Hear? A large-scale cross-corpus analysis
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Why the Body Comes First: Effects of Experimenter Touch on Infants' Word Finding
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In: Faculty Journal Articles (2015)
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Asymmetry of onsets and codas in language acquisition: Implications for phonological theories
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In: Theses and Dissertations Available from ProQuest (2015)
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The Edge Factor in Early Word Segmentation: Utterance-Level Prosody Enables Word Form Extraction by 6-Month-Olds
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