Claudia S. Bianchini, Léa Chèvrefils, Claire Danet, Patrick Doan, Morgane Rébulard, Adrien Contesse, D. Boutet
{"title":"手语中的编码运动:Typannot方法","authors":"Claudia S. Bianchini, Léa Chèvrefils, Claire Danet, Patrick Doan, Morgane Rébulard, Adrien Contesse, D. Boutet","doi":"10.1145/3212721.3212808","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":330867,"journal":{"name":"Proceedings of the 5th International Conference on Movement and Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Coding Movement in Sign Languages: the Typannot Approach\",\"authors\":\"Claudia S. Bianchini, Léa Chèvrefils, Claire Danet, Patrick Doan, Morgane Rébulard, Adrien Contesse, D. Boutet\",\"doi\":\"10.1145/3212721.3212808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":330867,\"journal\":{\"name\":\"Proceedings of the 5th International Conference on Movement and Computing\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 5th International Conference on Movement and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3212721.3212808\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Conference on Movement and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3212721.3212808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coding Movement in Sign Languages: the Typannot Approach
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.