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Si l’épopée est, d’une certaine manière, du mythe transposé en Histoire (et singulièrement en histoire des origines d’une société), dans un monde dont les acteurs sont, au moins partiellement, des hommes, le héros épique se présente comme un être doublement orienté, à la fois terrestre (combattant, époux, membre d’un lignage...) et exemplaire, soumis à la transcendance du destin et incarnation des schémas de pensée qui servent par ailleurs à exprimer et à expliquer les structures et les tensi...

Genre ou plutôt forme fictionnelle et poétique profondément originale au regard de la tradition épique antique ou de ses avatars modernes, texte déroutant entre récit et chant, l’épopée médiévale exige une approche particulière pour qu’en soient saisis les enjeux, les évolutions et les permanences. Aliscans, chanson de geste de la fin du XIIe s., représente une sorte d’étape seconde au sein du cycle dans lequel elle prend place. Par rapport aux œuvres premières – au sens de la transmission manuscrite – que sont La Chanson de Roland ou La Chanson de Guillaume, elle apparaît comme une réécriture, ou tout simplement une « écriture », une organisation réfléchie de la matière épique donnée dans le Guillaume, son modèle. Invités à une rencontre à l’ENS, des spécialistes de la Chanson de geste se sont proposés de dessiner les linéaments d’une définition. Les communications ont offert un large éventail de points de vue et de thèmes qui permettaient non seulement de saisir la diversité et la richesse du genre, mais aussi de mettre en perspective Aliscans au sein d’un vaste ensemble, débordant ainsi largement le seul intérêt d’une préparation à l’agrégation dont elle est une des œuvres au programme.

National audience

(poster); International audience; Two 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.4.12.07slo

International audience

International audience; The aim of this paper is to uncover formational features emerging with the conventionalization of recurrent gestures (Ladewig 2014, Müller 2017), in terms of their physiological bases and their relation to function. We thus illustrate how the joint limits of at least one of the segments (head, shoulder, arm, forearm, hand or fingers) and articulatory constraints between segments, are key to the stabilization of gestures’ form and function. We chose to focus on a specific composite gesture, the shrug, in order to conduct a cross-linguistic kinesiological analysis of gesture forms and their association to function. A cross-linguistic investigation was conducted on a collection of prototypical shrugs captured in context in English, French, Russian, German and French sign language (Polimod project, Cienki & Irishkhanova 2018, CoLaJE project, Morgenstern & Parisse, 2012).In order to identify the formational and functional invariant features of this composite gesture, we annotated all the extracts using a kinesiological coding system based on the form and the function of the gestures in context (Boutet 2001; Boutet et al., 2016). Our results indicated that there are associations between the uses of specific formational components and specific functions across languages.The complex formational pattern of the shrug, which comprises the open fingers, hands, arms, lifted shoulders and the tilting of the head, is supported by an association between form and function. Thus, throughout young children’s gestural development over time, shrugs are first used to refer to absence with the hands (palm up and extension of the forearm), then affective stance (“I don’t care” with the forearms, shoulder lift) and then epistemic stance (with head tilts) (Beaupoil & Debras, 2018). On a formational and structural level, in both our child and adult data, a core feature of the shrug was found to be related to the articulation of the arm’s movement, circulating along the upper limb. This core feature is related to the generic expression of incapacity. As the flow of the gesture ascends to the shoulders, it is transferred into a shoulder lift which expresses more subjectivity and stance. As it descends to the palms, it is transferred into an exterior rotation of the forearms (opening gesture) and into an extension that ends in a supination (palm up configuration) which expresses absence or non-intervention. We found cross-linguistic typological differences in the use of the various segments (hand, arm, forearm, hand, shoulder, head), in their combination and their amplitude.This study of a recurrent gesture illustrates how the articulatory constraints between segments can restrict and structure the formational/physiological expansion of recurrent gestures by enclosing them in a stabilized frame. Human physiology and the productivity of its constraints are a key factor in the conventionalization of gestures and thus in the dynamic process that transforms sensori-motor experience into symbolic communicative representation via continual human interaction.ReferencesBeaupoil-Hourdel P. & Debras C. (2017). Developing communicative postures: The emergence of shrugging in child communication. Language Interaction & Acquisition (LIA) 8(1), p. 91-118.Boutet, D. (2001). Approche morpho-dynamique du sens dans la gestuelle conversationnelle. Université de Paris VIII, Paris.Boutet, D., Morgenstern A., Cienki A. (2016). Grammatical Aspect and Gesture in French: a kinesiological approach. Vestnik RUDN. 20, 3. 131-150.Cienki, A., & Iriskhanova, O. K. (2018). Aspectuality cross Languages Event construal in speech and gesture (John Benjamins). Amsterdam, Philadelphia: Alan Cienki & Olga K. Iriskhanova.Ladewig, S. (2014). Recurrent gestures. In C. Müller, A. Cienki, E. Fricke, S. Ladewig, D. McNeill & J. Bressem (Eds.), Body - Language - Communication (HSK) (Vol. 38.2, pp. 1558-1574): de Gruyter.Morgenstern, A., & Parisse, C. (2012). The Paris Corpus. Journal of French Language Studies, 22(Special Issue 01), 7-12.Müller, C. (2017). How recurrent gestures mean. Gesture, 16(2), 277-304.

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International audience; This article is based on the CIGALE project, an interdisciplinary research between digital art, linguistics, and theater on motion capture and interaction with artistic, co-speech and expressive gestures. The aim of this project is to explore an interactive gestural dialogue between human and virtual actors. We will explain how our artistic modalities deal with space, time, and movement in a particular way to achieve our specific artistic goal: to encourage the emergence of a gestural interaction between human and virtual actor, thus giving the feeling of a "living" improvisation while exploring the lineaments of the aesthetics of improvisation. First, we will describe the design and development process of InterACTE, an artistic installation serving as a device for improvised gestural interaction between a spectator (human actor) and a digital partner (virtual actor). Then, from seven recorded videos of interactions between the virtual actor and human actor, we will present the interdisciplinary study we conducted using first, an artistic approach, and second, a linguistic approach.

(poster); International audience; Non-manual actions, and more specifically facial actions (FA) can be found in all Sign Languages (SL). Those actions involve all the different facial parts and can have various and intricate linguistic relations with manual signs. Unlike in vocal languages, FA in SL provide more meaning than simple expressions of feelings and emotions. Yet non-manual parameters are among the most unknown formal features in SL studies. During the past 30 years, some studies have started questioning the meanings and linguistic values and the relations between manual and non-manual signs (Crashborn et al. 2008; Crashborn & Bank 2014); more recently, SL corpora have been analysed, segmented, and transcribed to help study FA (Vogst-Svenden 2008; Bergman et al. 2008; Sutton-Spence & Day 2008).Moreover, to fill the lack of an annotation system for FA, a few manual annotation systems have integrated facial glyphs, such as HamNoSys (Prillwitz et al. 1989) and SignWriting (Sutton 1995). On one hand, HamNoSys has been developed to describe all existing SLs at a phonetic level; it allows a formal, linear, highly detailed and searchable description of manual parameters. As for non-manual parameters, HamNoSys offers the replacement of hands by another articulators. Non-manual parameters can be written as “eyes” or “mouth” and described by the same symbols developed for hands (Hanke 2004). Unfortunately only a limited number of manual symbols can be translated into FA and the annotation system remains incomplete. On the other hand, SignWriting describes SL with iconic symbols placed in a 2D space representing the signer’s body. Facial expressions are divided into mouth, eyes, nose, eyebrows, etc., and are drawn in a circular “head” much like emoticons. SignWriting offers a detailed description of posture and actions of non-manual parameters, but does not ensure compatibility with the most common annotation software used by SL linguists (e.g., ELAN).Typannot, a interdisciplinary project led by linguists, designers, and developers, which aims to set up a complete transcription system for SL that includes every SL parameter (handshape, localisation, movement, FA), has developed a different methodology. As mentioned earlier, FA have various linguistic values (mouthings, adverbial mouth gestures, semantically empty, enacting, whole face) and also include prosody and emotional meanings. In this regard, they can be more variable and signer-related than manual parameters. To offer the best annotation tool, Typannot approach has been to define facial parameters and all their possible tangible configurations. The goal is to set up the most efficient, simple, yet complete and universal formula to describe all possible FA.This formula is based on a 3-dimensional grid. Indeed all the different configurations of FA can be described by its X, Y, Z axis position. As a result, all FA can be described and encoded using a restricted list of 39 qualifiers. Based on this model and to help reduce the annotation process, a set of generic glyphs has been developed. Each qualifier has its own symbolic “generic” glyph. This methodical decomposition of all facial components enables a precise and accurate transcription of a complex FA using only a few glyphs.This formula and its generic glyphs have gone through a series of tests and revisions. Recently, an 18m20s long FA corpus of two deaf signers has been recorded using two different cameras. The first one, RGB HQ, is used to capture a high quality image and the second, infrared Kinect, is used to captured the depth. The latter was linked with Brekel Proface 2 (Leong et al. 2015), a 3D animation software that enables an automatic recognition of FA. This corpus has been fully annotated using Typannot generic glyphs. These annotations have enabled the validation of the general structure of Typannot FA formula and to identify some minor corrections to be made. For instance, it has been shown that the description of the air used to puff out or suck in cheeks is too restrictive and the description of the opening and closure of the eyelids is too unnecessarily precise.When those changes are implemented, our next task will be to develop a morphological glyphic system that will combine the different generic glyphs used for each facial parameter into one unique morphological glyph. This means that for any given FA, all the information contained in Typannot descriptive formula will be contained within one legible glyph. Some early research and work has already begun on this topic, but needs further development before providing a statement on its typographic structure. When this system is completed, it will be released with its own virtual keyboard (Typannot Keyboard, currently in development for handshapes) to help transcription and improve annotation processes.Bibliography:-Chételat-Pelé, E. (2010). Les Gestes Non Manuels en Langue des Signes Française ; Annotation, analyse et formalisation : application aux mouvements des sourcils et aux clignements des yeux. Université de Provence – Aix-Marseille I.-Crasborn, O., van der Kooij, E., Waters, D., Woll, B., & Mesch, J. (2008). Frequency distribution and spreading behavior of different types of mouth actions in three sign languages. Sign Language & Linguistics, 11(1), 45-67.-Crasborn, O.A., & Bank, R. (2014). An annotation scheme for the linguistic study of mouth actions in sign languages. http://repository.ubn.ru.nl/handle/2066/132960-Fontana, S. (2008). Mouth actions as gesture in sign language. Gesture, 8(1), 104-123.-Hanke, T. (2004). HamNoSys - Representing sign language data in language resources and language processing contexts. In Workshop on the Representation and Processing of Sign Languages on the occasion of the Fourth International Conference on Language Resources and Evaluation (p. 1-6).-Leong, C.W., Chen, L., Feng, G., Lee, C.M., & Mulholland, M. (2015). Utilizing depth sensors for analyzing multimodal presentations: Hardware, software and toolkits (p. 547-556). Proceedings of the 2015 ACM International Conference on Multimodal Interaction, ACM.-Prillwitz, S., Leven, R., Zienert, H., Hanke, T., & Henning, J. (1989). Hamburg notation system for sign languages: an introductory guide. Signum Press, Hamburg.-Sandler, W. (2009). Symbiotic symbolization by hand and mouth in sign language. Semiotica, 2009(174), 241-275. http://doi.org/10.1515/semi.2009.035-Sutton, V. (1995). Lessons in Sign Writing: textbook. DAC, La Jolla (CA).-Sutton-Spence, R., & Boyes-Braem, P. (2001). The hands are the head of the mouth: the mouth as articulator in sign languages. Signum Press, Hamburg

International audience

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see publication #024 - HAL‑02552935[conferenza annullata causa Covid]; International audience; The transcription of sign languages (SL) should take into account the gestural nature of these languages and, above all, why many typefont systems (e.g., HamNoSys, SignWriting) failed in establish themselves as a transcription tool (e.g., given the focus on the hands and the ego centered frame of reference). Gesturing sets all the segments of the upper limb in motion according to degrees of freedom, particular amplitudes and a series of intrinsic frames of reference centered on each segment. Typannot, the typefont system presented here, is based on these characteristics and integrates them into a structural hierarchy with an informational level corresponding to the features (characters), gathered in a level of glyphs composed. Typannot usability is ensured by respecting four design principles (genericity, modularity, legibility/readability and inscriptibility) and the use of a data entry interfaces managing these information levels. In order to illustrate the use of this font, analyses of the handshapes and proper location of the hand show the influence of practical gestures on symbolic gestures (i.e., SL signs). Considering the still cumbersome annotation time that such a transcription system imposes, the objective is to allow a “gestural dictation”, a direct transcription from motion capture data. This perspective should also facilitate the transcription of all the so called co verbal gestures of any vocal language.; Transcrire les langues des signes (LS) nécessite de prendre en considération leur nature gestuelle et de comprendre les raisons (parmi lesquelles centration sur les mains et utilisation d’un cadre de référence égocentré) pour lesquelles des systèmes typographiques (HamNoSys, SignWriting) ont échoué à s’imposer comme outil de transcription. La gestualité met en mouvement tous les segments du membre supérieur selon des degrés de liberté, en fonction d’amplitudes particulières et à travers une série de cadres de référence intrinsèque centrée sur chaque segment. Typannot, le système typographique présenté ici, repose sur ces caractéristiques et les intègre dans une hiérarchie structurelle ménageant un niveau informationnel correspondant aux traits (caractères), rassemblés dans un niveau de glyphes composés. La facilité d’utilisation de Typannot est assurée par le respect de quatre principes de conception (généricité, modularité, lisibilité et inscriptibilité) et l’utilisation d’une interface de saisie ménageant ces niveaux d’informations. Afin d’illustrer l’usage de Typannot, ont été menée des analyses portant sur les configurations et l’emplacement propre de la main, qui montrent l’influence de la gestualité praxique sur la gestualité symbolique (c.-à-d. les signes des LS). Vue la durée d’annotation encore très importante qu’un tel système de transcription impose, l’objectif est de permettre une "dictée gestuelle", une transcription directe à partir des données de capture de mouvement. Cette perspective devrait aussi faciliter la transcription de l’ensemble des gestes dits co-verbaux de n’importe quelle langue vocale.

International audience

Scholare-ISBN 2261-2424; International audience; The transcription of sign languages (SL) should take into account the gestural nature of these languages and, above all, why many typefont systems (e.g., HamNoSys, SignWriting) failed in establish themselves as a transcription tool (e.g., given the focus on the hands and the ego-centered frame of reference). Gesturing sets all the segments of the upper limb in motion according to degrees of freedom, particular amplitudes and a series of intrinsic frames of reference centered on each segment. Typannot, the typefont system presented here, is based on these characteristics and integrates them into a structural hierarchy with an informational level corresponding to the features (characters), gathered in a level of glyphs composed. Typannot usability is ensured by respecting four design principles (genericity, modularity, legibility/readability and inscriptibility) and the use of a data entry interfaces managing these information levels. In order to illustrate the use of this font, analyses of the handshapes and proper location of the hand show the influence of practical gestures on symbolic gestures (i.e., SL signs). Considering the still cumbersome annotation time that such a transcription system imposes, the objective is to allow a “gestural dictation”, a direct transcription from motion capture data. This perspective should also facilitate the transcription of all the so-called co-verbal gestures of any vocal language.; Transcrire les langues des signes (LS) nécessite de prendre en considération leur nature gestuelle et de comprendre les raisons (parmi lesquelles centration sur les mains et utilisation d'un cadre de référence égocentré) pour lesquelles des systèmes typographiques (HamNoSys, SignWriting) ont échoué à s'imposer comme outil de transcription. La gestualité met en mouvement tous les segments du membre supérieur selon des degrés de liberté, en fonction d'amplitudes particulières et à travers une série de cadres de référence intrinsèque centrée sur chaque segment. Typannot, le système typographique présenté ici, repose sur ces caractéristiques et les intègre dans une hiérarchie structurelle ménageant un niveau informationnel correspondant aux traits (caractères), rassemblés dans un niveau de glyphes composés. La facilité d'utilisation de Typannot est assurée par le respect de quatre principes de conception (généricité, modularité, lisibilité et inscriptibilité) et l'utilisation d'une interface de saisie ménageant ces niveaux d'informations. Afin d'illustrer l'usage de Typannot, ont été menée des analyses portant sur les configurations et l'emplacement propre de la main, qui montrent l'influence de la gestualité praxique sur la gestualité symbolique (c.-à-d. les signes des LS). Vue la durée d'annotation encore très importante qu'un tel système de transcription impose, l'objectif est de permettre une "dictée gestuelle", une transcription directe à partir des données de capture de mouvement. Cette perspective devrait aussi faciliter la transcription de l'ensemble des gestes dits co-verbaux de n'importe quelle langue vocale.; La trascrizione delle lingue dei segni (LS) richiede di considerare sia la loro natura gestuale che di comprendere le ragioni (incluso il centraggio sulle mani e l'uso di un quadro di riferimento egocentrico) per cui i sistemi tipografici (HamNoSys, SignWriting) non sono riusciti ad affermarsi come strumento di trascrizione. I gesti mettono in movimento tutti i segmenti dell'arto superiore in base ai gradi di libertà e le loro ampiezze particolari, tramite una serie di strutture di riferimento intrinseche, centrate su ciascun segmento. Typannot, il sistema tipografico qui presentato, si basa su queste caratteristiche e le integra in una gerarchia strutturale fornendo un livello di informazione corrispondente ai tratti (caratteri), raccolti in un livello di glifi composti. La facilità d'uso di Typannot è assicurata dal rispetto di quattro principi di progettazione (generalità, modularità, leggibilità e scrivibilità) e dall'uso di un'interfaccia di input che gestisce questi livelli di informazione. Al fine di illustrare l'uso di Typannot, sono state condotte analisi sulle configurazioni e sulla posizione corretta della mano, che mostrano l'influenza dei gesti concreti sui gesti simbolici (cioè i segni della LS). Dato il tempo di annotazione ancora molto importante richiesto da un tale sistema di trascrizione, l'obiettivo ulteriore è permettere una "dettatura gestuale", una trascrizione diretta dai dati di motion capture. Questa prospettiva dovrebbe anche facilitare la trascrizione di tutti i cosiddetti gesti co-verbali di qualsiasi linguaggio vocale.