312,569 research outputs found

    How sentence processing sheds light on mixed language creation

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    International audienceAuer (1999) and O'Shannessy (2012) suggest that codeswitching can become conventionalized, i.e., what is dubbed a "fused lect", and eventually give rise to a "mixed language". In this paper I propose that the study of sentence processing can shed light on this process. I discuss recent experimental data from a typologically rare form of mixing, variably termed "fused lect" (Adamou 2010) and "unevenly mixed language" (Adamou and Granqvist 2015), characterized by the conventionalized use of Turkish verbs together with Turkish morphology in a Romani environment. Specifically, Adamou and Shen (2019) conducted two on-line experiments, a picture choice task with sentence auditory stimuli (37 participants) and a word recognition task in sentence context (49 participants). Results from these experiments indicate that language switching costs depend on the degree of conventionalization and support usage-based approaches to language processing. I argue that these findings also lend support to the categorization of fused lects as an intermediate form between codeswitching and mixed languages

    L' épave Arles-Rhône 5, un nouveau chaland gallo-romain

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    International audienceL’épave Arles-Rhône 5 se trouve dans le Rhône, à Arles, en rive droite du fleuve, juste en face du Musée départemental Arles antique, entre les points kilométriques fluviaux1 284,500 et 285,500 (Fig. 1 et2). Disposée de façon approximativement parallèle à la berge (avec une orientation de 60/240°), l’épave est distante de celle-ci d’environ 8-10 m. Elle repose entre 4 et 8 m de profondeur, suivant la pente naturelle de la rive, par 15 à 20° de gîte. Elle fut découverte au début de l’été 200 lors d’une fouille de sauvetage mise en place et conduite par L. Long (Drassm/MC) à la suite de la construction d’un appontement (installation de ducs d’Albe2) par la Compagnie National du Rhône (CNR). L’expertise des vestiges menée lors de cette intervention a conclu à un état d conservation exceptionnelle et entière d’un chaland gallo-romain de même type qu’Arles-Rhône 3 (Marlier (dir.) 2014)

    La dispersion moderne de la bibliothèque monastique du Mont Saint-Michel (XVIe-XXIe siècle)

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    International audienceColloque international « Autour de la Bibliothèque virtuelle du Mont Saint-Michel. État des recherches sur l'ancienne bibliothèque monastique », Avranches - Mont Saint-Michel, 5-7 septembre 2018

    Crises des modèles? Agricultures, recompositions territoriales et relations villes-campagnes

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    International audienc

    Frontière

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    International audienc

    Senza caratteri adeguati, nessun vantaggio nella trascrizione e nei confronti

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    (poster)International audienceTwo main issues are still at stake for the transcription of gestures (i.e., co speech gestures and SL signs): i/ the time used to transcribe; and ii/ a sole system for these two kinds of transcriptions (Slobin et al., 2001). The time needed to annotate gestural phenomena restricts drastically the size of the corpus and therefore the possible generalizations; on the other side, the lack of a common transcription system makes difficult any comparison across studies of sign or gesture forms (see the description of “pointing gestures with a functional point of view” [Kita, 2003] and of “buoys in SL” [Liddell, 2003]) and means of expression (for example, many co-speech gestures introduced in SL discourse). This fact increases the differences between a “genuine” linguistic production and the co-speech gestures (Schembri et al., 2005; Goldin-Meadow & Brentari, 2017) and sometimes even essentializing these differences (Singleton et al., 1995; McNeill, 2015).A formal transcription system designed for SL (developed by the Typannot project) - but available for co-speech gestures as well - depicts each segment (hand, forearm, arm and shoulder) of the upper limb, palm orientation, handshapes and non-manual parameters (including mouth actions, facial expressions, head and torso positions). Each articulator is associated to a different OpenType font (e.g., Typannot_HandShape font, Typannot_MouthAction font, etc.) belonging to a specific font family (Boutet et al., 2018). Every character (in Unicode sense) of a Typannot_font contains only one specific information (for example, fingers, shape, angle and closeness between fingers are provided for handshapes; Bianchini et al., 2018) necessary to describe all the features of an articulator. An advanced system of typographic ligature allows the user to see a single “holistic” glyph containing every feature, assuring searchability in a readable way.Because of their formal approach, using these Typannot_fonts allows: i/ a comparison between SL and gestures/mimics in multimodal discourses; and ii/ in SL, detailed sub-parameter queries, e.g., about the angle of a segment according to a peculiar degree of freedom (e.g., full extension of the hand) and up to the relations among segments - it is even possible to discriminate pointing forms, regardless of a finger. A corpus of multimodal French discourses and French Sign Language (LSF), of several minutes each, has been transcribed (with ELAN) using the Typannot_fonts in manual and semi-automatic ways. This last kind of transcription in Typannot_fonts is made filming the speaker wearing an IMU device, and processing the video with OpenFace (Baltrušaitis et al., 2018).In this talk, we will present this family fonts system, its structure, the annotated features, the possible queries made at two levels, the characters themselves and their ligatured glyphs. Some transcribed data and preliminary results will be exposed, focusing on the time used for transcription, by comparison of the ratio between manual and semi-automatic processing.We propose, as a side event to the conference, to set up a tutorial session (3 hours, small group) to learn how to use the Typannot transcription environment. BIBLIOGRAPHYBaltrušaitis T., Zadeh A., Chong Lim Y, Morency L-P. 2018. OpenFace 2.0: facial behavior analysis toolkit. 13th IEEE Intl Conf. Automatic Face & Gesture Recognition (FG 2018): 59-66. doi.org/10.1109/FG.2018.00019Bianchini C.S., Chèvrefils L., Danet C., Doan P., Rébulard M., Contesse A., Boutet D. 2018. Coding movement in sign languages: the Typannot approach. Proc. ACM 5th Intl Conf. Movement and Computing (MoCo'18), sect. 1(#9): 1-8.Boutet D., Doan P., Bianchini C.S., Danet C., Goguely T., Rébulard M. 2018. Systèmes graphématiques et écritures des langues signées. in “Signatures: (essais en) sémiotique de l’écriture” (J.M. Klinkenberg, S. Polis eds). Signata, 9: 391-426.Goldin-Meadow S., Brentari D. 2017. Gesture, sign and language: the coming of age of sign language and gesture studies. Behavioral and Brain Sciences, 40(e46): 1-82.Kita S. 2003. Pointing: a foundational building block of human communication. in "Pointing: where language, culture, and cognition meet" (S. Kita ed.). Erlbaum (Mahwah NJ): 1-8.Liddell S.K. 2003. Grammar, gesture, and meaning in American Sign Language. Cambridge University Press.McNeill D. (2015). Why we gesture. in: "Why we gesture: the surprising role of hand movements in communication". Cambridge University Press: 3-20. doi.org/10.1017/CBO9781316480526.002Schembri A., Jones C., Burnham D. 2005. Comparing action gestures and classifier verbs of motion: evidence from Australian Sign Language, Taiwan Sign Language, and nonsigners’ gestures without speech. Journal of Deaf Studies and Deaf Education, 10(3), 272-290. doi.org/10.1093/deafed/eni029Singleton J.L., Goldin-Meadow S., McNeill D. 1995. The cataclysmic break between gesticulation and sign: evidence against a unified continuum of gestural communication. in: "Language, gesture, and space" (K. Emmorey, J. Reilly eds). Hillsdale NJ: Lawrence Erlbaum Associates Publishers: 287-311.Slobin DI., Hoiting N., Anthony M., Biederman Y., Kuntze M., Lindert R., Pyers J., Thumann H., Weinberg A. 2001. Sign language transcription at the level of meaning components: the Berkeley Transcription System (BTS). Sign Language & Linguistics 4(1-2): 63-104. doi.org/10.1075/sll.4.12.07sl

    Introduction générale

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    Collection Éducation, formation et lien social.International audienc

    The acceptability of telemedicine cabins by the students

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    CNRS 4, FNEGE 3, HCERES BInternational audienceTelemedicine solutions are invading our daily lives, raising a major issue concerning the personalization of remote consultation and trust in the physician’s Competence, Integrity and Benevolence (Trusting Beliefs). The aim of this study is to extend the existing Technology-Acceptance-Model (TAM) using the concept of Trusting Beliefs and Perceived Personalization. To test the model, a quantitative approach using existing scales has been selected. A survey was administered to students from several French business schools and the sample of 158 students was analysed using a Partial Least Approach. Findings highlight the key role of Trusting Beliefs in Perceived-Personalization. While two of the three dimensions (Benevolence and Integrity) of Trusting Beliefs theory have no influence on the Intention-to-Use, Competence has a direct, positive and significant impact on Intention-to-Use a Telemedicine Cabin. The relationship between the variables of the TAM is validated, except for Perceived-Ease-of-Use, which does not impact the Intention-to-Use a Telemedicine cabin

    The acceptability of telemedicine cabins by the students

    No full text
    CNRS 4, FNEGE 3, HCERES BInternational audienceTelemedicine solutions are invading our daily lives, raising a major issue concerning the personalization of remote consultation and trust in the physician’s Competence, Integrity and Benevolence (Trusting Beliefs). The aim of this study is to extend the existing Technology-Acceptance-Model (TAM) using the concept of Trusting Beliefs and Perceived Personalization. To test the model, a quantitative approach using existing scales has been selected. A survey was administered to students from several French business schools and the sample of 158 students was analysed using a Partial Least Approach. Findings highlight the key role of Trusting Beliefs in Perceived-Personalization. While two of the three dimensions (Benevolence and Integrity) of Trusting Beliefs theory have no influence on the Intention-to-Use, Competence has a direct, positive and significant impact on Intention-to-Use a Telemedicine Cabin. The relationship between the variables of the TAM is validated, except for Perceived-Ease-of-Use, which does not impact the Intention-to-Use a Telemedicine cabin
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