DOCSLIB.ORG

A Descriptive Grammar of Sign Language of the Netherlands

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Descriptive Grammar of Sign Language of the Netherlands A descriptive grammar of Sign Language of the Netherlands Published by LOT phone: +31 20 525 2461 Kloveniersburgwal 48 1012 CX Amsterdam e-mail: [email protected] The Netherlands http://www.lotschool.nl Cover illustration: © Elisa Hartog Fotografie Concept by Ulrika Klomp, inspired by Stokpic on Pixabay Map of the Netherlands by Clker-Free-Vector-Images on Pixabay Hand model Kristina Klomp ISBN: 978-94-6093-370-7 DOI: https://dx.medra.org/10.48273/LOT0585 NUR: 616 Copyright © 2021: Ulrika Klomp. All rights reserved. Images from Crasborn et al. (2020), with and without added symbols, are licensed under the CC-BY-NC-SA 4.0 license. A descriptive grammar of Sign Language of the Netherlands ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ter overstaan van een door het College van Promoties ingestelde commissie, in het openbaar te verdedigen in de Aula der Universiteit op vrijdag 5 maart 2021, te 14.00 uur door Ulrika Klomp geboren te Amsterdam Promotiecommissie Promotor: dr. R. Pfau Universiteit van Amsterdam Copromotor: prof. dr. E.M. van den Bogaerde Universiteit van Amsterdam Overige leden: dr. E.H. van Lier Universiteit van Amsterdam dr. C. Tijsseling Koninklijke Kentalis prof. dr. P. Perniss Universität zu Köln prof. dr. P.C. Hengeveld Universiteit van Amsterdam prof. dr. F. Gobbo Universiteit van Amsterdam prof. dr. O.A. Crasborn Radboud Universiteit dr. F. Roelofsen Universiteit van Amsterdam Faculteit der Geesteswetenschappen This project has received funding from the European Commission within Horizon 2020 Reflective Society 2015, Research and Innovation actions, grant agreement No 693349. Table of Contents Acknowledgements.......................................................................................... 23 Author contributions ...................................................................................... 27 Notation conventions ...................................................................................... 29 0. Introduction ................................................................................................... 33 0.1. The SIGN-HUB project ........................................................................................ 33 0.2. The book version and the platform version .............................................. 35 0.3. Procedure of writing and methodology ...................................................... 36 0.3.1. The author and the data........................................................................ 36 0.3.2. Methodological choices made by the SIGN-HUB project ......... 38 0.3.3. A word on variation ................................................................................ 40 0.4. The structure and use of this grammar ....................................................... 40 Part 1: Socio-historical Background Chapter 1. History ............................................................................................ 45 1.1. Deaf education in the 18th and 19th century ........................................... 45 1.2. The first signs of NGT .......................................................................................... 48 1.3. The deaf community in the 19th and 20th century ................................ 49 1.4. The start of sign language research in the 20th century ....................... 50 1.5. Historical relations with other sign languages ......................................... 50 Information on Data and Consultants................................................................... 51 Chapter 2. The sign language community ................................................ 53 2.1. Community characteristics ............................................................................... 53 2.1.1. Surinam and the former Netherlands Antilles ............................ 53 2.1.2 The sign language community in the Netherlands ..................... 54 2.2. Sign language users .............................................................................................. 54 6 | 2.2.1. Early onset deaf people ......................................................................... 54 2.2.2. Hard of hearing people .......................................................................... 56 2.2.3. Sudden and late deafened people ..................................................... 56 2.2.4. Deafblind people ...................................................................................... 57 2.2.5. Hearing signers ........................................................................................ 58 2.3. Deaf culture ............................................................................................................. 59 2.3.1. Cultural values and traditions ............................................................ 60 2.3.2. Theater and poetry ................................................................................. 60 2.3.3. Storytelling and the sign choir ........................................................... 62 2.3.4. Annual events ............................................................................................ 62 2.3.5. Media ............................................................................................................ 63 2.3.6. Associations for the deaf ...................................................................... 64 2.4. Deaf education ....................................................................................................... 66 Information on Data and Consultants................................................................... 67 Chapter 3. Status ............................................................................................... 69 3.1. Current legislation ................................................................................................ 69 3.2. Language policy ..................................................................................................... 69 3.3. Language attitudes ............................................................................................... 70 Information on Data and Consultants................................................................... 71 Chapter 4. Linguistic study ............................................................................ 73 4.1. Grammatical description ................................................................................... 73 4.2. Lexicographic work ............................................................................................. 75 4.3. Corpora ..................................................................................................................... 75 4.4. Sociolinguistic variation..................................................................................... 76 Information on Data and Consultants................................................................... 76 Part 2: Phonology Chapter 1. Sublexical structure ................................................................... 79 1.1. Active articulators ................................................................................................ 79 | 7 1.1.1. Phonemic handshapes ........................................................................... 80 1.1.1.1. Selected fingers ..................................................................................... 91 1.1.1.2. Finger configuration ........................................................................... 94 1.1.2. Orientation ................................................................................................. 96 1.1.3. The manual alphabet and number signs ..................................... 100 1.1.4. Other active articulators .................................................................... 102 1.2. Location ................................................................................................................. 102 1.3. Movement ............................................................................................................. 105 1.3.1. Path movement ..................................................................................... 106 1.3.2. Secondary movement ......................................................................... 109 1.4. Two-handed signs ............................................................................................. 111 1.4.1. Symmetrical signs ................................................................................ 114 1.4.2. Asymmetrical signs .............................................................................. 114 1.5. Non-manuals ........................................................................................................ 116 1.5.1. Mouth gestures ...................................................................................... 116 1.5.2. Mouthings ................................................................................................ 118 1.5.3. Other non-manuals .............................................................................. 120 Information on Data and Consultants................................................................ 122 Chapter 2. Prosody ........................................................................................ 127 2.1. The lexical level .................................................................................................. 127 2.1.1. Syllable .....................................................................................................
Load more

Recommended publications
  • The Signing Space for the Synthesis of Directional Verbs in NGT
    The signing space for the synthesis of directional verbs in NGT Shani E. Mende-Gillings Layout: typeset by the author using LATEX. Cover illustration: Unknown artist The signing space for the synthesis of directional verbs in NGT Shani E. Mende-Gillings 11319836 Bachelor thesis Credits: 18 EC Bachelor Kunstmatige Intelligentie University of Amsterdam Faculty of Science Science Park 904 1098 XH Amsterdam Supervisor dr. F. Roelofsen Institute for Logic, Language and Computation Faculty of Science University of Amsterdam Science Park 107 1098 XG Amsterdam 26 June 2020 Acknowledgements I would like to thank my supervisor Floris Roelofsen for his guidance during this project. I am also very grateful to John Glauert and Richard Kennaway for proving valuable insight into SiGML and the JASigning software. Special thanks go to Inge Zwitserlood, Onno Crasborn and Johan Ros for providing the database of encoded NGT signs, without which this project would not have been possible. Last, but not least, I would also like to thank Marijke Scheffener for providing evaluation material and valuable feedback on the program. Preface This paper describes an individual contribution to a larger project executed in close collaboration with [1] and [2]. The first parts of these three papers describe the overall project and were jointly written, making them largely identical. Section 1.2 describes the global research question, and sections 2 and 3 provide the- oretical context and set up a hypothesis. Section 5.1.1 shows the overall program created, including the components of the other projects, and section 5.2.1 evaluates the result. These previously mentioned chap- ters and sections have been written in joint collaboration with [1] and [2] An introduction to and motivation for the overall project are provided in section 1.
    [Show full text]
  • Sign Classification in Sign Language Corpora with Deep Neural Networks
    Sign Classification in Sign Language Corpora with Deep Neural Networks Lionel Pigou, Mieke Van Herreweghe, Joni Dambre Ghent University flionel.pigou, mieke.vanherreweghe, [email protected] Abstract Automatic and unconstrained sign language recognition (SLR) in image sequences remains a challenging problem. The variety of signers, backgrounds, sign executions and signer positions makes the development of SLR systems very challenging. Current methods try to alleviate this complexity by extracting engineered features to detect hand shapes, hand trajectories and facial expressions as an intermediate step for SLR. Our goal is to approach SLR based on feature learning rather than feature engineering. We tackle SLR using the recent advances in the domain of deep learning with deep neural networks. The problem is approached by classifying isolated signs from the Corpus VGT (Flemish Sign Language Corpus) and the Corpus NGT (Dutch Sign Language Corpus). Furthermore, we investigate cross-domain feature learning to boost the performance to cope with the fewer Corpus VGT annotations. Keywords: sign language recognition, deep learning, neural networks 1. Introduction In previous work (Pigou et al., 2015), we showed that deep neural networks are very successful for gesture recognition SLR systems have many different use cases: corpus anno- and gesture spotting in spatiotemporal data. Our developed tation, in hospitals, as a personal sign language learning system is able to recognize 20 different Italian gestures (i.e., assistant or translating daily conversations between signers emblems). We achieved a classification accuracy of 97.23% and non-signers to name a few. Unfortunately, unconstrained in the Chalearn 2014 Looking At People gesture spotting SLR remains a big challenge.
    [Show full text]
  • Gesture and Sign Language Recognition with Temporal Residual Networks
    Gesture and Sign Language Recognition with Temporal Residual Networks Lionel Pigou, Mieke Van Herreweghe and Joni Dambre Ghent University {lionel.pigou, mieke.vanherreweghe, joni.dambre}@ugent.be Abstract SLR using recurrent CNNs [6]. A task that is closely related to SLR is gesture recog- Gesture and sign language recognition in a continuous nition. Deep neural networks have proven to be success- video stream is a challenging task, especially with a large ful for this problem, given a small vocabulary (20 gestures) vocabulary. In this work, we approach this as a framewise [22, 30] and/or with a multi-modal approach [24, 18]. classification problem. We tackle it using temporal con- In this work, we investigate large vocabulary gesture volutions and recent advances in the deep learning field recognition and SLR using deep neural networks with up- like residual networks, batch normalization and exponen- to-date architectures, regularization techniques and training tial linear units (ELUs). The models are evaluated on methods. To achieve this, we approach the problem as a three different datasets: the Dutch Sign Language Corpus continuous framewise classification task, where the tempo- (Corpus NGT), the Flemish Sign Language Corpus (Cor- ral locations of gestures and signs are not given during eval- pus VGT) and the ChaLearn LAP RGB-D Continuous Ges- uation. The models are tested on the Dutch Sign Language ture Dataset (ConGD). We achieve a 73.5% top-10 accu- Corpus (Corpus NGT) [4, 5], the Flemish Sign Language racy for 100 signs with the Corpus NGT, 56.4% with the Corpus (Corpus VGT) [27] and the ChaLearn LAP RGB-D Corpus VGT and a mean Jaccard index of 0.316 with the Continuous Gesture Dataset (ConGD) [28].
    [Show full text]
  • A Lexical Comparison of South African Sign Language and Potential Lexifier Languages
    A lexical comparison of South African Sign Language and potential lexifier languages by Andries van Niekerk Thesis presented in partial fulfilment of the requirements for the degree Masters in General Linguistics at the University of Stellenbosch Supervisors: Dr Kate Huddlestone & Prof Anne Baker Faculty of Arts and Social Sciences Department of General Linguistics March, 2020 Stellenbosch University https://scholar.sun.ac.za DECLARATION By submitting this thesis electronically, I declare that the entirety of the work contained therein is my own, original work, that I am the sole author thereof (save to the extent explicitly otherwise stated), that reproduction and publication thereof by Stellenbosch University will not infringe any third party rights and that I have not previously in its entirety or in part submitted it for obtaining any qualification. Andries van Niekerk March 2020 Copyright © 2020 University of Stellenbosch All rights reserved 1 Stellenbosch University https://scholar.sun.ac.za ABSTRACT South Africa’s history of segregation was a large contributing factor for lexical variation in South African Sign Language (SASL) to come about. Foreign sign languages certainly had a presence in the history of deaf education; however, the degree of influence foreign sign languages has on SASL today is what this study has aimed to determine. There have been very limited studies on the presence of loan signs in SASL and none have included extensive variation. This study investigates signs from 20 different schools for the deaf and compares them with signs from six other sign languages and the Paget Gorman Sign System (PGSS). A list of lemmas was created that included the commonly used list of lemmas from Woodward (2003).
    [Show full text]
  • The Signed Languages of Indonesia: an Enigma
    DigitalResources Electronic Survey Report 2014-005 ® The Signed Languages of Indonesia: An Enigma Hope M. Hurlbut The Signed Languages of Indonesia: An Enigma Hope M. Hurlbut SIL International® 2014 SIL Electronic Survey Report 2014-005, April 2014 © 2014 SIL International® All rights reserved 1 2 Abstract In 2003–2005, SIL International undertook a lexicostatistical survey of the signed languages of Indonesia. Wordlists and stories were collected from each of the nineteen states where one or more schools for the Deaf were run privately or by the government. The wordlists were video recorded and transcribed by hand using the SignWriting orthography. The results of the wordlist comparisons point out the need for intelligibility testing between users of the various varieties of Indonesian Sign Language. Intelligibility testing should be carried out sometime in at least eleven of the nineteen states where the similarity between the signs in the list is low. This paper focuses on the results of the lexicostatistical survey. There are at least two signed languages in use in Indonesia, Indonesian Sign Language and Bengkala Sign Language. Bengkala Sign Language is an isolect found in northern Bali in the village of Bengkala where there is a high proportion of Deaf among the inhabitants. It has been called Bali Sign Language in the past, but since it seems to be more or less confined to the village of Bengkala, it seems better to call it Bengkala Sign Language. The rest of the Deaf on the island use a form of Indonesian Sign Language. At the time of the survey there were two Deaf youth from Bengkala going to school in the Deaf school (or a Deaf class) in Singaraja which is about 17 kilometers from Bengkala Village.
    [Show full text]
  • Typology of Signed Languages: Differentiation Through Kinship Terminology Erin Wilkinson
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of New Mexico University of New Mexico UNM Digital Repository Linguistics ETDs Electronic Theses and Dissertations 7-1-2009 Typology of Signed Languages: Differentiation through Kinship Terminology Erin Wilkinson Follow this and additional works at: https://digitalrepository.unm.edu/ling_etds Recommended Citation Wilkinson, Erin. "Typology of Signed Languages: Differentiation through Kinship Terminology." (2009). https://digitalrepository.unm.edu/ling_etds/40 This Dissertation is brought to you for free and open access by the Electronic Theses and Dissertations at UNM Digital Repository. It has been accepted for inclusion in Linguistics ETDs by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected]. TYPOLOGY OF SIGNED LANGUAGES: DIFFERENTIATION THROUGH KINSHIP TERMINOLOGY BY ERIN LAINE WILKINSON B.A., Language Studies, Wellesley College, 1999 M.A., Linguistics, Gallaudet University, 2001 DISSERTATION Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Linguistics The University of New Mexico Albuquerque, New Mexico August, 2009 ©2009, Erin Laine Wilkinson ALL RIGHTS RESERVED iii DEDICATION To my mother iv ACKNOWLEDGMENTS Many thanks to Barbara Pennacchi for kick starting me on my dissertation by giving me a room at her house, cooking me dinner, and making Italian coffee in Rome during November 2007. Your endless support, patience, and thoughtful discussions are gratefully taken into my heart, and I truly appreciate what you have done for me. I heartily acknowledge Dr. William Croft, my advisor, for continuing to encourage me through the long number of months writing and rewriting these chapters.
    [Show full text]
  • What Corpus-Based Research on Negation in Auslan and PJM Tells Us About Building and Using Sign Language Corpora
    What Corpus-Based Research on Negation in Auslan and PJM Tells Us About Building and Using Sign Language Corpora Anna Kuder1, Joanna Filipczak1, Piotr Mostowski1, Paweł Rutkowski1, Trevor Johnston2 1Section for Sign Linguistics, Faculty of the Polish Studies, University of Warsaw, Krakowskie Przedmieście 26/28, 00-927 Warsaw, Poland 2Department of Linguistics, Faculty of Human Sciences, Macquarie University, Sydney, NSW, Australia, 2109 {anna.kuder, j.filipczak, piotr.mostowski, p.rutkowski}@uw.edu.pl, [email protected] Abstract In this paper, we would like to discuss our current work on negation in Auslan (Australian Sign Language) and PJM (Polish Sign Language, polski język migowy) as an example of experience in using sign language corpus data for research purposes. We describe how we prepared the data for two detailed empirical studies, given similarities and differences between the Australian and Polish corpus projects. We present our findings on negation in both languages, which turn out to be surprisingly similar. At the same time, what the two corpus studies show seems to be quite different from many previous descriptions of sign language negation found in the literature. Some remarks on how to effectively plan and carry out the annotation process of sign language texts are outlined at the end of the present paper, as they might be helpful to other researchers working on designing a corpus. Our work leads to two main conclusions: (1) in many cases, usage data may not be easily reconciled with intuitions and assumptions about how sign languages function and what their grammatical characteristics are like, (2) in order to obtain representative and reliable data from large-scale corpora one needs to plan and carry out the annotation process very thoroughly.
    [Show full text]
  • Variation in Mouth Actions with Manual Signs (Chapter 2)
    PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/133714 Please be advised that this information was generated on 2021-10-01 and may be subject to change. The ubiquity of mouthings in NGT A corpus study Published by LOT phone: +31 30 253 6111 Trans 10 3512 JK Utrecht e-mail: [email protected] The Netherlands http://www.lotschool.nl Cover illustration: (stemmed) word cloud of this dissertation, from tagul.com. ISBN: 978-94-6093-158-1 NUR 616 Copyright © 2014: Richard Bank. All rights reserved. The ubiquity of mouthings in NGT A corpus study Proefschrift ter verkrijging van de graad van doctor aan de Radboud Universiteit Nijmegen op gezag van de rector magnificus prof. dr. Th. L. M. Engelen volgens besluit van het college van decanen in het openbaar te verdedigen op vrijdag 30 januari 2015 om 12.30 uur precies door Richard Bank Geboren op 1 augustus 1969 te Amsterdam Promotor: Prof. dr. Roeland van Hout Copromotor: Dr. Onno Crasborn Manuscriptcommissie: Prof. dr. Pieter Muysken Prof. dr. Jens Heßmann (Hochschule Magdeburg-Stendal, Duitsland) Prof. dr. Bencie Woll (DCAL, University College London, Groot-Brittannië) Table of contents Dankwoord ..................................................................................................................... ix Chapter 1: Introduction ........................................................................................ 1 1.1 Sign languages: a general introduction ..................................................................... 2 1.1.1 A short history of sign languages...................................................................... 3 1.1.2 Research and recognition .................................................................................. 4 1.1.3 The recent history of NGT ................................................................................ 5 1.1.4 Deaf education in the Netherlands and influence of spoken language .........
    [Show full text]
  • Sign Language Legislation in the European Union 4
    Sign Language Legislation in the European Union Mark Wheatley & Annika Pabsch European Union of the Deaf Brussels, Belgium 3 Sign Language Legislation in the European Union All rights reserved. No part of this book may be reproduced or transmitted by any person or entity, including internet search engines or retailers, in any form or by any means, electronic or mechanical, including photocopying, recording, scanning or by any information storage and retrieval system without the prior written permission of the authors. ISBN 978-90-816-3390-1 © European Union of the Deaf, September 2012. Printed at Brussels, Belgium. Design: Churchill’s I/S- www.churchills.dk This publication was sponsored by Significan’t Significan’t is a (Deaf and Sign Language led ) social business that was established in 2003 and its Managing Director, Jeff McWhinney, was the CEO of the British Deaf Association when it secured a verbal recognition of BSL as one of UK official languages by a Minister of the UK Government. SignVideo is committed to delivering the best service and support to its customers. Today SignVideo provides immediate access to high quality video relay service and video interpreters for health, public and voluntary services, transforming access and career prospects for Deaf people in employment and empowering Deaf entrepreneurs in their own businesses. www.signvideo.co.uk 4 Contents Welcome message by EUD President Berglind Stefánsdóttir ..................... 6 Foreword by Dr Ádám Kósa, MEP ................................................................
    [Show full text]
  • Sign Languages
    200-210 Sign languages 200 Arık, Engin: Describing motion events in sign languages. – PSiCL 46/4, 2010, 367-390. 201 Buceva, Pavlina; Čakărova, Krasimira: Za njakoi specifiki na žestomimičnija ezik, izpolzvan ot sluchouvredeni lica. – ESOL 7/1, 2009, 73-79 | On some specific features of the sign language used by children with hearing disorders. 202 Dammeyer, Jesper: Tegnsprogsforskning : om tegnsprogets bidrag til viden om sprog. – SSS 3/2, 2012, 31-46 | Sign language research : on the contribution of sign language to the knowledge of languages | E. ab | Electronic publ. 203 Deaf around the world : the impact of language / Ed. by Gaurav Mathur and Donna Jo Napoli. – Oxford : Oxford UP, 2011. – xviii, 398 p. 204 Fischer, Susan D.: Sign languages East and West. – (34), 3-15. 205 Formational units in sign languages / Ed. by Rachel Channon ; Harry van der Hulst. – Berlin : De Gruyter Mouton ; Nijmegen : Ishara Press, 2011. – vi, 346 p. – (Sign language typology ; 3) | Not analyzed. 206 Franklin, Amy; Giannakidou, Anastasia; Goldin-Meadow, Susan: Negation, questions, and structure building in a homesign system. – Cognition 118/3, 2011, 398-416. 207 Gebarentaalwetenschap : een inleiding / Onder red. van Anne E. Baker ; Beppie van den Bogaerde ; Roland Pfau ; Trude Schermer. – Deventer : Van Tricht, 2008. – 328 p. 208 Kendon, Adam: A history of the study of Australian Aboriginal sign languages. – (50), 383-402. 209 Kendon, Adam: Sign languages of Aboriginal Australia : cultural, semi- otic and communicative perspectives. – Cambridge : Cambridge UP, 2013. – 562 p. | First publ. 1988; cf. 629. 210 Kudła, Marcin: How to sign the other : on attributive ethnonyms in sign languages. – PFFJ 2014, 81-92 | Pol.
    [Show full text]
  • Sociolinguistics in European Deaf Communities
    Contributors IRIS ANTOONS Iris Antoons is a doctoral student in the Department of Germanic Lan- guages at the Vrije Universiteit Brussel, where she also received a Mas- ter’s degree in Germanic languages in 2000. She then worked for the Vlaams GebarentaalCentrum (Flemish Sign Language Center) on a proj- ect to develop teaching materials for courses in Flemish Sign Language. She is currently carrying out a research project on bimodal and bilingual language acquisition of prelingually deaf children, which is underwritten by the Fund for Scientific Research-Flanders. DIANE BOONEN In 1987 Diane Boonen began working for Fevlado, the Flemish Deaf As- sociation, as an administrative employee in one of the regional offices. She first became involved in linguistic research on Flemish Sign Language (VGT) when Myriam Vermeerbergen asked her to act as the main infor- mant for a study on prepositions in VGT in 1988.In1992 Boonen began teaching Flemish Sign Language in the Department of Germanic Lan- guages at the Vrije Universiteit Brussel. In the following five years she regularly participated in various research activities on the grammar of Flemish Sign Language. In 1997 Fevlado agreed to give her an opportu- nity to concentrate on the linguistic study and teaching of Flemish Sign Language, and she became a full-time collaborator of Vermeerbergen at the Vrije Universiteit Brussel. KRISTOF DE WEERDT Kristof De Weerdt is a second-generation, Deaf native signer. He began working for the English Department of Ghent University in October 1999 as a researcher in a project focusing on lexicographic aspects of Flemish Sign Language.
    [Show full text]
  • Collecting and Evaluating the CUNY ASL Corpus for Research On
    Collecting and Evaluating the CUNY ASL Corpus for Research on American Sign Language Animation Pengfei Lu Matt Huenerfauth Doctoral Program in Computer Science Department of Computer Science The Graduate Center, CUNY Queens College and Graduate Center City University of New York City University of New York (CUNY) 365 Fifth Ave, New York, NY 10016 65-30 Kissena Blvd, Flushing, NY 11367 [email protected] [email protected] Abstract While there is great potential for sign language animation generation software to improve the ac- cessibility of information for deaf individuals with low written-language literacy, the understanda- bility of current sign language animation systems is limited. Data-driven methodologies using annotated sign language corpora encoding detailed human movement have enabled some research- ers to address several key linguistic challenges in ASL generation. This article motivates and de- scribes our current research on collecting a motion-capture corpus of American Sign Language (ASL). As an evaluation of our motion-capture configuration, calibration, and recording protocol, we have conducted several rounds of evaluation studies with native ASL signers, and we have made use of our collected data to synthesize novel animations of ASL, which have also been eval- uated in experimental studies with native signers. 1 Introduction Sign languages are natural languages conveyed by movements of the hands, arms, torso, head, face, and eyes. There are different sign languages used around the world, and sign languages in different countries are not typically mutually intelligible. Further, the sign language in a country is often distinct from the spoken/written language in use in that country; a sign language is not merely a manual representation of the word order of the local spoken language.
    [Show full text]