Coding movement in sign languages: the Typannot approach
CS Bianchini, L Chèvrefils, C Danet, P Doan… - Proceedings of the 5th …, 2018 - dl.acm.org
CS Bianchini, L Chèvrefils, C Danet, P Doan, M Rébulard, A Contesse, D Boutet
Proceedings of the 5th International Conference on Movement and Computing, 2018•dl.acm.orgTypannot is an innovative transcription system (TranSys) for Sign Languages (SLs), based
on robust graphematic and coherent typographic formulas. It is characterized by readability,
writability, searchability, genericity and modularity. Typannot can be used to record
handshapes, mouth actions, facial expressions, initial locations (LOCini) and movements of
the upper limbs (MOV). For LOCini and MOV, Typannot uses intrinsic frames of reference
(iFoR) to describe the position of each segment (arm, forearm, hand) in terms of degrees of …
on robust graphematic and coherent typographic formulas. It is characterized by readability,
writability, searchability, genericity and modularity. Typannot can be used to record
handshapes, mouth actions, facial expressions, initial locations (LOCini) and movements of
the upper limbs (MOV). For LOCini and MOV, Typannot uses intrinsic frames of reference
(iFoR) to describe the position of each segment (arm, forearm, hand) in terms of degrees of …
Typannot is an innovative transcription system (TranSys) for Sign Languages (SLs), based on robust graphematic and coherent typographic formulas. It is characterized by readability, writability, searchability, genericity and modularity. Typannot can be used to record handshapes, mouth actions, facial expressions, initial locations (LOCini) and movements of the upper limbs (MOV). For LOCini and MOV, Typannot uses intrinsic frames of reference (iFoR) to describe the position of each segment (arm, forearm, hand) in terms of degrees of freedom (DoF). It assumes that the motion is subdivided into a complex moment of initial preparation, leading to the stabilization of a LOCini, and a subsequent phase of MOV deployment based on simple motor patterns. The goal of Typannot is not only to create a new TranSys, but also to provide an instrument to advance the knowledge about SLs. The observation of the SLs makes it possible to formulate various hypotheses, among which: 1) MOV follows a simple motor scheme that aims at minimizing motor control during MOV; 2) proximal→distal flows of MOV are predominant in SLs. Only the use of a TranSys based on iFoR and the description of the DoF makes it possible to explore the data in order to test these hypotheses.
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