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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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Does infant-directed speech help phonetic learning? A machine learning investigation
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In: ISSN: 0364-0213 ; EISSN: 1551-6709 ; Cognitive Science ; https://hal.archives-ouvertes.fr/hal-03080098 ; Cognitive Science, Wiley, 2021, 45 (5), ⟨10.1111/cogs.12946⟩ (2021)
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Abstract:
International audience ; A prominent hypothesis holds that by speaking to infants in infant-directed speech (IDS) as opposed to adult-directed speech (ADS), parents help them learn phonetic categories. Specifically, two characteristics of IDS have been claimed to facilitate learning: hyperarticulation, which makes the categories more separable and variability, which makes the generalization more robust. Here, we test the separability and robustness of vowel category learning on acoustic representations of speech uttered by Japanese adults in either ADS, IDS (addressed to 18-24 month olds) or read speech (RS). Separability is determined by means of a distance measure computed between the five short vowel categories of Japanese, while robustness is assessed by testing the ability of six different machine learning algorithms trained to classify vowels to generalize on stimuli spoken by a novel speaker in ADS. Using two different speech representations, we find that hyperarticulated speech, in the case of RS, can yield better separability, and that increased between-speaker variability in ADS, can yield, for some algorithms, more robust categories. However, these conclusions do not apply to IDS, which turned out to yield neither more separable nor more robust categories compared to ADS inputs. We discuss the usefulness of machine learning algorithms run on real data to test hypotheses about the functional role of IDS.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]; Adult-directed speech; Hyperarticulation; Infant-directed speech; Phonetic learning; Read speech; Speech variability
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URL: https://doi.org/10.1111/cogs.12946 https://hal.archives-ouvertes.fr/hal-03080098/document https://hal.archives-ouvertes.fr/hal-03080098/file/CognitiveScience.pdf https://hal.archives-ouvertes.fr/hal-03080098
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Does Infant-Directed Speech Help Phonetic Learning? A Machine Learning Investigation
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Why is Japanese not difficult to process?: A proposal to integrate parameter setting in Universal Grammar and parsing
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In: North East Linguistics Society (2020)
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Normalization may be ineffective for phonetic category learning ...
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Nasal Consonant Discrimination in Infant- and Adult-Directed Speech
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Normalization may be ineffective for phonetic category learning
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In: Proceedings of the Society for Computation in Linguistics (2019)
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Are Words Easier to Learn From Infant- Than Adult-Directed Speech? A Quantitative Corpus-Based Investigation
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In: ISSN: 0364-0213 ; EISSN: 1551-6709 ; Cognitive Science ; https://hal.archives-ouvertes.fr/hal-01888701 ; Cognitive Science, Wiley, 2018, 42 (5), pp.1586 - 1617. ⟨10.1111/cogs.12616⟩ (2018)
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The Role of Prosody and Speech Register in Word Segmentation: A Computational Modelling Perspective
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In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) ; https://hal.inria.fr/hal-01687451 ; Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Jul 2017, Vancouver, Canada. ⟨10.18653/v1/P17-2028⟩ (2017)
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Are words easier to learn from infant- than adult-directed speech? A quantitative corpus-based investigation ...
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Age-Dependent Effects of Catechol-O-Methyltransferase (COMT) Gene Val158Met Polymorphism on Language Function in Developing Children
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The acoustic salience of prosody trumps infants' acquired knowledge of language-specific prosodic patterns
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Auditory observation of infant-directed speech by mothers: experience-dependent interaction between language and emotion in the basal ganglia
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