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1
Frequency norms in Tashlhiyt, Part I
In: https://halshs.archives-ouvertes.fr/halshs-03511109 ; 2022 (2022)
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2
Investigating the locus of transposed-phoneme effects using cross-modal priming
In: ISSN: 0001-6918 ; EISSN: 1873-6297 ; Acta Psychologica ; https://hal.archives-ouvertes.fr/hal-03619856 ; Acta Psychologica, Elsevier, 2022, 226, pp.103578. ⟨10.1016/j.actpsy.2022.103578⟩ (2022)
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3
INGLIZ TILINING FONETIK VARIANTLARI ... : PHONETIC VARIATIONS IN ENGLISH LANGUAGE ...
Gulbahor Mahmudovna Qodirova. - : Central Asian Research Journal for Interdisciplinary Studies (CARJIS), 2022
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4
Segment Substitution of the French Rhotic /ʁ/ by Educated Edo-Bini French Bilinguals ...
Dr. Paschal Dada Omage PhD. - : Zenodo, 2022
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5
Segment Substitution of the French Rhotic /ʁ/ by Educated Edo-Bini French Bilinguals ...
Dr. Paschal Dada Omage PhD. - : Zenodo, 2022
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6
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling ...
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7
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling ...
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8
A Rule-Based Grapheme-to-Phoneme Conversion System
In: Applied Sciences; Volume 12; Issue 5; Pages: 2758 (2022)
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9
Success Is Not the Entire Story for a Scientific Theory: The Case of the Phonological Deficit Theory of Dyslexia
In: Brain Sciences; Volume 12; Issue 4; Pages: 425 (2022)
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10
PHONEME AND LETTER RELATIONS IN "DIWAN LUGHAT AL-TURK" ...
Misliddinova Malika. - : Zenodo, 2022
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11
PHONEME AND LETTER RELATIONS IN "DIWAN LUGHAT AL-TURK" ...
Misliddinova Malika. - : Zenodo, 2022
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12
Robust phoneme recognition for a speech therapy environment
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13
What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach
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14
Orthogonal neural codes for speech in the infant brain
In: ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.archives-ouvertes.fr/hal-03349785 ; Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2021, 118 (31), pp.e2020410118. ⟨10.1073/pnas.2020410118⟩ (2021)
Abstract: International audience ; Creating invariant representations from an everchanging speech signal is a major challenge for the human brain. Such an ability is particularly crucial for preverbal infants who must discover the phonological, lexical, and syntactic regularities of an extremely inconsistent signal in order to acquire language. Within the visual domain, an efficient neural solution to overcome variability consists in factorizing the input into a reduced set of orthogonal components. Here, we asked whether a similar decomposition strategy is used in early speech perception. Using a 256-channel electroencephalographic system, we recorded the neural responses of 3-mo-old infants to 120 natural consonant–vowel syllables with varying acoustic and phonetic profiles. Using multivariate pattern analyses, we show that syllables are factorized into distinct and orthogonal neural codes for consonants and vowels. Concerning consonants, we further demonstrate the existence of two stages of processing. A first phase is characterized by orthogonal and context-invariant neural codes for the dimensions of manner and place of articulation. Within the second stage, manner and place codes are integrated to recover the identity of the phoneme. We conclude that, despite the paucity of articulatory motor plans and speech production skills, pre-babbling infants are already equipped with a structured combinatorial code for speech analysis, which might account for the rapid pace of language acquisition during the first year.
Keyword: [SCCO.LING]Cognitive science/Linguistics; [SCCO.NEUR]Cognitive science/Neuroscience; ERP; infant; language; phoneme; speech
URL: https://hal.archives-ouvertes.fr/hal-03349785/file/Gennari_DehaeneLambertz_DecodingPhonemes_BioRxiv2020.pdf
https://hal.archives-ouvertes.fr/hal-03349785/document
https://doi.org/10.1073/pnas.2020410118
https://hal.archives-ouvertes.fr/hal-03349785
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15
Towards the prediction of the vocal tract shape from the sequence of phonemes to be articulated
In: iNTERSPEECH 2021 ; https://hal.inria.fr/hal-03360113 ; iNTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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16
Stem similarity modulates infants' acquisition of phonological alternations.
Sundara, Megha; White, James; Kim, Yun Jung. - : eScholarship, University of California, 2021
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17
Early Auditory Event-Related Potentials Are Modulated by Alphabetic Literacy Skills in Logographic Chinese Readers
In: ISSN: 1664-1078 ; Frontiers in Psychology ; https://hal.archives-ouvertes.fr/hal-03340213 ; Frontiers in Psychology, Frontiers, 2021, 12, pp.663166. ⟨10.3389/fpsyg.2021.663166⟩ (2021)
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18
Qu'est-ce que la forme sonore des énoncés ? ; : Les sons du français Comment décrire la forme sonore des énoncésLa prononciation des mots en contextePhrasé, accentuation et intonation
In: La grande Grammaire du français ; https://halshs.archives-ouvertes.fr/halshs-00748393 ; Abeillé, Anne; Godard, Danièle. La grande Grammaire du français, volume (2), Actes Sud, pp.2077-2090, 2021, La Grande Grammaire du Français - GGF 2, 978-2-330-14239-1 (2021)
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19
Phoneme-to-Audio Alignment with Recurrent Neural Networks for Speaking and Singing Voice
In: Proceedings of Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03552964 ; Proceedings of Interspeech 2021, International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.61-65, ⟨10.21437/interspeech.2021-1676⟩ ; https://www.interspeech2021.org/ (2021)
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20
Consonant-in-noise discrimination using an auditory model with different speech-based decision devices
In: 47th Annual Conference on Acoustics DAGA 2021 Wien ; DAGA ; https://hal.archives-ouvertes.fr/hal-03345050 ; DAGA, Aug 2021, Vienne, Austria. pp.298-301 ; https://www.daga2021.eu/ (2021)
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