Papers with LSF
A Low-Cost Motion Capture Corpus in French Sign Language for Interpreting Iconicity and Spatial Referencing Mechanisms (2022.lrec-1)
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| Challenge: | Existing tools for automatic translation of sign language videos into transcribed texts are limited. |
| Approach: | They propose to use deep learning methods to circumvent the use of models in spatial referencing recognition by a 3D skeleton and a software program to capture and post-process the LSF-SHELVES corpus. |
| Outcome: | The proposed system targets iconicity and spatial referencing in french sign language . it is light-weight and low-cost to collect data from a large panel of signers . |
Multidimensional Coding of Multimodal Languaging in Multi-Party Settings (2022.lrec-1)
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Christophe Parisse, Marion Blondel, Stéphanie Caët, Claire Danet, Coralie Vincent, Aliyah Morgenstern
| Challenge: | In natural language settings, many interactions include more than two speakers and real-life interpretation is based on all types of information available in all modalities. |
| Approach: | They propose to use a coding tool to analyze spontaneous interactions in family dinner settings. |
| Outcome: | The proposed method compares the language of two adults and three children in family dinner settings using either French, or French sign language. |
Rosetta-LSF: an Aligned Corpus of French Sign Language and French for Text-to-Sign Translation (2022.lrec-1)
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Elise Bertin-Lemée, Annelies Braffort, Camille Challant, Claire Danet, Boris Dauriac, Michael Filhol, Emmanuella Martinod, Jérémie Segouat
| Challenge: | a new corpus of french Sign Language (LSF) data is created to support future studies on the automatic translation of written French into LSF, rendered through the animation of a virtual signer. |
| Approach: | They propose to use a French Sign Language corpus called "Rosetta-LSF" it is intended to support studies on automatic translation of written French into LSF . |
| Outcome: | The proposed corpus supports future studies on automatic translation of written French into LSF, rendered through animation of a virtual signer. |
Extending AZee with Non-manual Gesture Rules for French Sign Language (2024.lrec-main)
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| Challenge: | Currently, Sign Languages (SLs) are under-resourced and are difficult to develop. |
| Approach: | They propose to extend AZee to formally represent Sign Language discourses, but also to animate them with a virtual signer. |
| Outcome: | The proposed model allows to formally represent Sign Language discourses, but also to animate them with a virtual signer. |
Elicitation protocol and material for a corpus of long prepared monologues in Sign Language (L18-1)
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| Challenge: | elicitation of long discourses is difficult in Sign Language, and is often a problem . e.g., elicitation of long texts is a technique that can be used to collect long discourse . |
| Approach: | They propose a protocol and two tasks to collect long discourse in Sign Language . they propose to ensure both are collected and prepared in the language . |
| Outcome: | The proposed protocol improves the produced data and the results of a test with LSF informants. |
Modeling French Sign Language: a proposal for a semantically compositional system (L18-1)
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| Challenge: | Several studies have proposed linguistic models to describe sign languages, but none have succeeded to describe the specificities of SL. |
| Approach: | They propose a linguistic approach to formalize the sign language (SL) they propose to take into account linguistic properties of the SL while respecting constraints of a modelisation process. |
| Outcome: | The proposed model takes into account linguistic properties of the sign language while respecting constraints of a modelisation process. |
LSF-ANIMAL: A Motion Capture Corpus in French Sign Language Designed for the Animation of Signing Avatars (2020.lrec-1)
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| Challenge: | Signing avatars are often procedurally animated, resulting in robotic and unnatural movements, which are therefore rejected by the Deaf community. |
| Approach: | They propose to use a French Sign Language corpus to create an avatar that can be edited from motion capture data to create new signs and utterances. |
| Outcome: | The proposed corpus is based on a french Sign Language (LSF) corpus composed of captured signs and sentences. |