@inproceedings{duarte-gibet-2010-heterogeneous,
title = "Heterogeneous Data Sources for Signed Language Analysis and Synthesis: The {S}ign{C}om Project",
author = "Duarte, Kyle and
Gibet, Sylvie",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L10-1289/",
abstract = "This paper describes how heterogeneous data sources captured in the SignCom project may be used for the analysis and synthesis of French Sign Language (LSF) utterances. The captured data combine video data and multimodal motion capture (mocap) data, including body and hand movements as well as facial expressions. These data are pre-processed, synchronized, and enriched by text annotations of signed language elicitation sessions. The addition of mocap data to traditional data structures provides additional phonetic data to linguists who desire to better understand the various parts of signs (handshape, movement, orientation, etc.) to very exacting levels, as well as their interactions and relative timings. We show how the phonologies of hand configurations and articulator movements may be studied using signal processing and statistical analysis tools to highlight regularities or temporal schemata between the different modalities. Finally, mocap data allows us to replay signs using a computer animation engine, specifically editing and rearranging movements and configurations in order to create novel utterances."
}
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<abstract>This paper describes how heterogeneous data sources captured in the SignCom project may be used for the analysis and synthesis of French Sign Language (LSF) utterances. The captured data combine video data and multimodal motion capture (mocap) data, including body and hand movements as well as facial expressions. These data are pre-processed, synchronized, and enriched by text annotations of signed language elicitation sessions. The addition of mocap data to traditional data structures provides additional phonetic data to linguists who desire to better understand the various parts of signs (handshape, movement, orientation, etc.) to very exacting levels, as well as their interactions and relative timings. We show how the phonologies of hand configurations and articulator movements may be studied using signal processing and statistical analysis tools to highlight regularities or temporal schemata between the different modalities. Finally, mocap data allows us to replay signs using a computer animation engine, specifically editing and rearranging movements and configurations in order to create novel utterances.</abstract>
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%0 Conference Proceedings
%T Heterogeneous Data Sources for Signed Language Analysis and Synthesis: The SignCom Project
%A Duarte, Kyle
%A Gibet, Sylvie
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F duarte-gibet-2010-heterogeneous
%X This paper describes how heterogeneous data sources captured in the SignCom project may be used for the analysis and synthesis of French Sign Language (LSF) utterances. The captured data combine video data and multimodal motion capture (mocap) data, including body and hand movements as well as facial expressions. These data are pre-processed, synchronized, and enriched by text annotations of signed language elicitation sessions. The addition of mocap data to traditional data structures provides additional phonetic data to linguists who desire to better understand the various parts of signs (handshape, movement, orientation, etc.) to very exacting levels, as well as their interactions and relative timings. We show how the phonologies of hand configurations and articulator movements may be studied using signal processing and statistical analysis tools to highlight regularities or temporal schemata between the different modalities. Finally, mocap data allows us to replay signs using a computer animation engine, specifically editing and rearranging movements and configurations in order to create novel utterances.
%U https://aclanthology.org/L10-1289/
Markdown (Informal)
[Heterogeneous Data Sources for Signed Language Analysis and Synthesis: The SignCom Project](https://aclanthology.org/L10-1289/) (Duarte & Gibet, LREC 2010)
ACL