Christophe Collet

Also published as: C. Collet


Design and Evaluation for a Prototype of an Online Tool to Access Mathematics Notions in Sign Language
Camille Nadal | Christophe Collet
Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives

The Sign’Maths project aims at giving access to pedagogical resources in Sign Language (SL). It will provide Deaf students and teachers with mathematics vocabulary in SL, this in order to contribute to the standardisation of the vocabulary used at school. The work conducted led to Sign’Maths, an online interactive tool that gives Deaf students access to mathematics definitions in SL. A group of mathematics teachers for Deafs and teachers experts in SL collaborated to create signs to express mathematics concepts, and to produce videos of definitions, examples and illustrations for these concepts. In parallel, we are working on the conception and the design of Sign’Maths software and user interface. Our research work investigated ways to include SL in pedagogical resources in order to present information but also to navigate through the content. User tests revealed that users appreciate the use of SL in a pedagogical resource. However, they pointed out that SL content should be complemented with French to support bilingual education. Our final solution takes advantage of the complementarity of SL, French and visual content to provide an interface that will suit users no matter what their education background is. Future work will investigate a tool for text and signs’ search within Sign’Maths.


Supporting Sign Languages Exploratory Linguistics with an Automatization of the Annotation Process (Vers un traitement automatique en soutien d’une linguistique exploratoire des Langues des Signes) [in French]
Rémi Dubot | Arturo Curiel | Christophe Collet
Proceedings of TALN 2014 (Volume 2: Short Papers)


Sign Language Lexical Recognition With Propositional Dynamic Logic
Arturo Curiel | Christophe Collet
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)


Semi-Automatic Sign Language Corpora Annotation using Lexical Representations of Signs
Matilde Gonzalez | Michael Filhol | Christophe Collet
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Nowadays many researches focus on the automatic recognition of sign language. High recognition rates are achieved using lot of training data. This data is, generally, collected by manual annotating SL video corpus. However this is time consuming and the results depend on the annotators knowledge. In this work we intend to assist the annotation in terms of glosses which consist on writing down the sign meaning sign for sign thanks to automatic video processing techniques. In this case using learning data is not suitable since at the first step it will be needed to manually annotate the corpus. Also the context dependency of signs and the co-articulation effect in continuous SL make the collection of learning data very difficult. Here we present a novel approach which uses lexical representations of sign to overcome these problems and image processing techniques to match sign performances to sign representations. Signs are described using Zeebede (ZBD) which is a descriptor of signs that considers the high variability of signs. A ZBD database is used to stock signs and can be queried using several characteristics. From a video corpus sequence features are extracted using a robust body part tracking approach and a semi-automatic sign segmentation algorithm. Evaluation has shown the performances and limitation of the proposed approach.


Toward an Annotation Software for Video of Sign Language, Including Image Processing Tools and Signing Space Modelling
A. Braffort | A. Choisier | C. Collet | P. Dalle | F. Gianni | F. Lenseigne | J. Segouat
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)