This article presents a new French Sign Language (LSF) corpus called “Rosetta-LSF”. It was created to support future studies on the automatic translation of written French into LSF, rendered through the animation of a virtual signer. An overview of the field highlights the importance of a quality representation of LSF. In order to obtain quality animations understandable by signers, it must surpass the simple “gloss transcription” of the LSF lexical units to use in the discourse. To achieve this, we designed a corpus composed of four types of aligned data, and evaluated its usability. These are: news headlines in French, translations of these headlines into LSF in the form of videos showing animations of a virtual signer, gloss annotations of the “traditional” type—although including additional information on the context in which each gestural unit is performed as well as their potential for adaptation to another context—and AZee representations of the videos, i.e. formal expressions capturing the necessary and sufficient linguistic information. This article describes this data, exhibiting an example from the corpus. It is available online for public research.

Sign Languages (SLs) are the visuo-gestural languages practised by the deaf communities. Research on SLs requires to build, to analyse and to use corpora. The aim of this paper is to present various kinds of new uses of SL corpora. The way data are used take advantage of the new capabilities of annotation software for visualisation, numerical annotation, and processing. The nature of the data can be video-based or motion capture-based. The aims of the studies include language analysis, animation processing, and evaluation. We describe here some LIMSI’s studies, and some studies from other laboratories as examples.

Cet article présente Dicta-Sign, un projet de recherche sur le traitement automatique des langues des signes (LS), qui aborde un grand nombre de questions de recherche : linguistique de corpus, modélisation linguistique, reconnaissance et génération automatique. L’objectif de ce projet est de réaliser trois applications prototypes destinées aux usagers sourds : un traducteur de termes de LS à LS, un outil de recherche par l’exemple et un Wiki en LS. Pour cela, quatre corpus comparables de cinq heures de dialogue seront produits et analysés. De plus, des avancées significatives sont attendues dans le domaine des outils d’annotation. Dans ce projet, le LIMSI est en charge de l’élaboration des modèles linguistiques et participe aux aspects corpus et génération automatique. Nous nous proposons d’illustrer l’état d’avancement de Dicta-Sign au travers de vidéos extraites du corpus et de démonstrations des outils de traitement et de génération d’animations de signeur virtuel.

This paper presents a study on synchronization of linguistic annotation and numerical data on a video corpus of French Sign Language. We detail the methodology and sketches out the potential observations that can be provided by such a kind of mixed annotation. The corpus is composed of three views: close-up, frontal and top. Some image processing has been performed on each video in order to provide global information on the movement of the signers. That consists of the size and position of a bounding box surrounding the signer. Linguists have studied this corpus and have provided annotations on iconic structures, such as "personal transfers" (role shifts). We used an annotation software, ANVIL, to synchronize linguistic annotation and numerical data. This new approach of annotation seems promising for automatic detection of linguistic phenomena, such as classification of the signs according to their size in the signing space, and detection of some iconic structures. Our first results must be consolidated and extended on the whole corpus. The next step will consist of designing automatic processes in order to assist SL annotation.