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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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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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| 12 |
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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| 15 |
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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| 17 |
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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| 19 |
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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Abstract:
International audience ; Voice activity detection is the task of detecting speech regions in a given audio stream or recording. First, we design a neural network combining trainable filters and recurrent layers to tackle voice activity detection directly from the waveform. Experiments on the challenging DIHARD dataset show that the proposed end-to-end model reaches state-of-the-art performance and outperforms a variant where trainable filters are replaced by standard cepstral coefficients. Our second contribution aims at making the proposed voice activity detection model robust to domain mismatch. To that end, a domain classification branch is added to the network and trained in an adversarial manner. The same DIHARD dataset, drawn from 11 different domains is used for evaluation under two scenarios. In the in-domain scenario where the training and test sets cover the exact same domains, we show that the domain-adversarial approach does not degrade performance of the proposed end-to-end model. In the out-domain scenario where the test domain is different from training domains, it brings a relative improvement of more than 10%. Finally, our last contribution is the provision of a fully reproducible open-source pipeline than can be easily adapted to other datasets.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
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URL: https://hal.archives-ouvertes.fr/hal-02989502
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| 20 |
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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