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How much does prosody help word segmentation? A simulation study on infant-directed speech
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03498888 ; Cognition, Elsevier, 2022, 219, pp.104961. ⟨10.1016/j.cognition.2021.104961⟩ (2022)
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Is there a bilingual disadvantage for word segmentation? A computational modeling approach
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498905 ; Journal of Child Language, Cambridge University Press (CUP), 2021, pp.1-28. ⟨10.1017/S0305000921000568⟩ (2021)
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SCALa: A blueprint for computational models of language acquisition in social context
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.inria.fr/hal-03373586 ; Cognition, Elsevier, 2021, 213, pp.104779. ⟨10.1016/j.cognition.2021.104779⟩ (2021)
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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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Toward Cumulative Cognitive Science: A Comparison of Meta-Analysis, Mega-Analysis, and Hybrid Approaches
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-03498941 ; Open Mind, MIT Press, 2021, 5, pp.154-173. ⟨10.1162/opmi_a_00048⟩ (2021)
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Socioeconomic status correlates with measures of Language Environment Analysis (LENA) system: a meta-analysis
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498959 ; Journal of Child Language, Cambridge University Press (CUP), In press, pp.1-15. ⟨10.1017/S0305000921000441⟩ (2021)
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The effect of Crianza Positiva e-messaging program on adult-child language interactions
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In: Behavioral Public Policy ; https://hal.archives-ouvertes.fr/hal-03498848 ; Behavioral Public Policy, 2021 (2021)
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| 8 |
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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Abstract:
International audience ; Purpose Recording young children's vocalizations through wearables is a promising method to assess language development. However, accurately and rapidly annotating these files remains challenging. Online crowdsourcing with the collaboration of citizen scientists could be a feasible solution. In this article, we assess the extent to which citizen scientists' annotations align with those gathered in the lab for recordings collected from young children. Method Segments identified by Language ENvironment Analysis as produced by the key child were extracted from one daylong recording for each of 20 participants: 10 low-risk control children and 10 children diagnosed with Angelman syndrome, a neurogenetic syndrome characterized by severe language impairments. Speech samples were annotated by trained annotators in the laboratory as well as by citizen scientists on Zooniverse. All annotators assigned one of five labels to each sample: Canonical, Noncanonical, Crying, Laughing, and Junk. This allowed the derivation of two child-level vocalization metrics: the Linguistic Proportion and the Canonical Proportion. Results At the segment level, Zooniverse classifications had moderate precision and recall. More importantly, the Linguistic Proportion and the Canonical Proportion derived from Zooniverse annotations were highly correlated with those derived from laboratory annotations. Conclusions Annotations obtained through a citizen science platform can help us overcome challenges posed by the process of annotating daylong speech recordings. Particularly when used in composites or derived metrics, such annotations can be used to investigate early markers of language delays.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; [SCCO.PSYC]Cognitive science/Psychology
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URL: https://hal.archives-ouvertes.fr/hal-03498946/document
https://hal.archives-ouvertes.fr/hal-03498946/file/2021_Semenzin_JSLHR.pdf
https://hal.archives-ouvertes.fr/hal-03498946
https://doi.org/10.1044/2021_JSLHR-20-00661
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Seshat: A tool for managing and verifying annotation campaigns of audio data
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In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02496041 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.6976-6982 (2020)
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An open-source voice type classifier for child-centered daylong recordings
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In: Interspeech 2020 - Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02989487 ; Interspeech 2020 - Conference of the International Speech Communication Association, Oct 2020, Shanghai / Virtual, China (2020)
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| 11 |
Language input and outcome variation as a test of theory plausibility: The case of early phonological acquisition
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In: ISSN: 0273-2297 ; EISSN: 1090-2406 ; Developmental Review ; https://hal.archives-ouvertes.fr/hal-03096004 ; Developmental Review, Elsevier, 2020, 57, pp.100914. ⟨10.1016/j.dr.2020.100914⟩ (2020)
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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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| 13 |
Infant-directed input and literacy effects on phonological processing: Non-word repetition scores among the Tsimane’
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In: ISSN: 1932-6203 ; EISSN: 1932-6203 ; PLoS ONE ; https://hal.archives-ouvertes.fr/hal-03096010 ; PLoS ONE, Public Library of Science, 2020, 15 (9), ⟨10.1371/journal.pone.0237702⟩ (2020)
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| 14 |
Addressing Publication Bias in Meta-Analysis
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In: ISSN: 0044-3409 ; Journal of Psychology / Zeitschrift für Psychologie ; https://hal.archives-ouvertes.fr/hal-03096016 ; Journal of Psychology / Zeitschrift für Psychologie, Hogrefe, 2020, 228 (1), pp.50-61. ⟨10.1027/2151-2604/a000393⟩ (2020)
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A thorough evaluation of the Language Environment Analysis (LENATM) system
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In: ISSN: 1554-351X ; EISSN: 1554-3528 ; Behavior Research Methods ; https://hal.archives-ouvertes.fr/hal-02989519 ; Behavior Research Methods, Psychonomic Society, Inc, 2020, ⟨10.31219/osf.io/mxr8s⟩ (2020)
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| 16 |
A thorough evaluation of the Language Environment Analysis (LENA) system
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In: ISSN: 1554-351X ; EISSN: 1554-3528 ; Behavior Research Methods ; https://hal.archives-ouvertes.fr/hal-03095997 ; Behavior Research Methods, Psychonomic Society, Inc, 2020, 53 (2), pp.467-486. ⟨10.3758/s13428-020-01393-5⟩ (2020)
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Speaker detection in the wild: Lessons learned from JSALT 2019
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In: Odyssey 2020 The Speaker and Language Recognition Workshop ; https://hal.archives-ouvertes.fr/hal-02417632 ; Odyssey 2020 The Speaker and Language Recognition Workshop, Nov 2020, Tokyo, Japan (2020)
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| 18 |
Longform recordings : Opportunities and challenges ; Enregistrements de longue durée: Opportunités et défis
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In: Actes des 2èmes journées scientifiques du Groupement de Recherche Linguistique Informatique Formelle et de Terrain (LIFT). ; LIFT 2020 - 2èmes journées scientifiques du Groupement de Recherche "Linguistique informatique, formelle et de terrain" ; https://hal.archives-ouvertes.fr/hal-03047153 ; LIFT 2020 - 2èmes journées scientifiques du Groupement de Recherche "Linguistique informatique, formelle et de terrain", Dec 2020, Montrouge / Virtual, France. pp.64-71 (2020)
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End-to-end Domain-Adversarial Voice Activity Detection
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In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-02989502 ; Interspeech 2020, Nov 2020, Shanghai, France (2020)
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Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-02274050 ; Open Mind, MIT Press, 2019, 3, pp.13-22. ⟨10.1162/opmi_a_00022⟩ (2019)
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