Analysis of Notation Systems for Machine Translation of Sign Languages

Total Page:16

File Type:pdf, Size:1020Kb

Analysis of Notation Systems for Machine Translation of Sign Languages Analysis of Notation Systems for Machine Translation of Sign Languages Submitted in partial fulfilment of the requirements of the degree of Bachelor of Science (Honours) of Rhodes University Jessica Jeanne Hutchinson Grahamstown, South Africa November 2012 Abstract Machine translation of sign languages is complicated by the fact that there are few stan- dards for sign languages, both in terms of the actual languages used by signers within regions and dialogue groups, and also in terms of the notations with which sign languages are represented in written form. A standard textual representation of sign languages would aid in optimising the translation process. This area of research still needs to determine the best, most efficient and scalable tech- niques for translation of sign languages. Being a young field of research, there is still great scope for introducing new techniques, or greatly improving on previous techniques, which makes comparing and evaluating the techniques difficult to do. The methods used are factors which contribute to the process of translation and need to be considered in an evaluation of optimising translation systems. This project analyses sign language notation systems; what systems exists, what data is currently available, and which of them might be best suited for machine translation purposes. The question being asked is how using a textual representation of signs could aid machine translation, and which notation would best suit the task. A small corpus of SignWriting data was built and this notation was shown to be the most accessible. The data was cleaned and run through a statistical machine translation system. The results had limitations, but overall are comparable to other translation systems, showing that translation using a notation is possible, but can be greatly improved upon. ACM Computing Classification System Thesis classifcation under the ACM Computing Classifcation System (1998 version, valid through 2012) I.2.7 [Natural Language Processing]: Language parsing and understanding, Machine translation, Text analysis J.5 [Arts and Humanities] Language translation, Linguistics General Terms : Sign Language, Machine Translation Acknowledgements I would like to acknowledge the financial and technical support of Telkom, Tellabs, Stortech,Genband, Easttel, Bright Ideas 39 and THRIP throughthe Telkom Centre of Excellence in the Department of Computer Science at Rhodes University. Contents 1 Introduction 1 2 Background 3 2.1 Sign Language . 3 2.1.1 3D Signing Space . 3 2.1.2 Use of Time . 4 2.1.3 Classifier Predicates . 5 2.1.4 Phonetics and Phonology . 5 2.1.5 Variation . 7 2.1.6 Notations . 7 2.2 Machine Translation . 7 2.2.1 Rule-based Systems . 8 2.2.2 Empirical Systems . 9 2.3 Machine Translation of Sign Languages . 10 2.3.1 Text-To-Sign Systems . 10 2.3.2 Sign-To-Text Translation . 11 i CONTENTS ii 3 Notations 13 3.1 Stokoe . 13 3.2 Gloss . 14 3.3 Hamburg Notation System . 15 3.4 SignWriting . 16 3.5 Other Representation Systems . 18 4 Corpus Construction and Translation 22 4.1 Data Requirements . 22 4.2 Acquiring Data . 23 4.3 Data Cleaning and Preparation . 24 4.3.1 Language model . 26 4.4 Machine Translation . 26 5 Conclusion 29 5.1 Future work . 29 List of Figures 2.1 The ASL sign for \dog" [1] . 4 2.2 The ASL sign for \mother" on the left, and for \father" on the right . 5 2.3 Machine Translation Architectures [14] . 8 3.1 An Example of the Stokoe system - an extract from Goldilocks and the Three Bears[21] . 14 3.2 An Example of Gloss Notation [22] . 15 3.3 An Example of HamNoSys using the same passage as in Figure 3.1 . 16 3.4 An Example of SignWriting, with the same passage as in Figure 3.1 . 17 3.5 An example of a sign in the MSW encoding [26] . 18 3.6 A passage of the bible in ASLSJ . 19 4.1 Luke 3:8 in American Sign Language . 28 iii List of Tables iv Chapter 1 Introduction Machine translation is one of the oldest areas of research in Computer Science[16]. Sign Linguistics, on the other hand, is a relatively new field of study in the area of Linguistics, and the combination - machine translation of sign languages - is less than twenty years old[23]. Sign languages as languages have not been studied as extensively as spoken languages, and there is still much to be learned about them. There are few standards for sign lan- guages, both in terms of the actual languages used by signers within regions and dialogue groups, and also in terms of the notations with which sign languages are represented in written form. The second factor affects the first: sign languages remain localised to small regions, as there is little technology that allows widespread use of a language or dialect. Visual communication tools such as Skype or Google Hangouts offer a partial solution to this problem, but there are still network-related and hardware-related difficulties that make such communication more difficult than text communication, especially in regions where there is less access to good technology. A standard textual representation of sign languages would provide an easier communication medium to sign language users and if more communication is happening across regions, language use and dialects also become more standardised [4]. Standardisation of language aids in machine translation of that language, as there are fewer variations, contributing to a smaller error margin. Correspondingly, machine trans- lation can assist with the standardisation of language, as it can provide greater accessibil- ity for communication, even between language groups (such as between spoken languages and signed languages, or between two signed languages). 1 2 A number of systems for translation between signed and spoken languages have been built or prototyped, with a range of focuses and using a variety of techniques, some suc- cessful and some not yet successful, all with their advantages and disadvantages. Many research projects are currently in progress, researching better techniques for data process- ing, translation models, gesture recognition, sign synthesis. Projects in this area have not yet reached a point where they can start improving on existing systems, optimising them, and deploying them; the general research question is still \can this be done?" The current goal for this area of research would be to get to that point where the question of whether translation can be achieved no longer needs to be asked and where the best, most efficient and scalable techniques for translation are known. To get to that point, however, a lot more research needs to be done on which options are the best. Being a young field of research, there is still great scope for introducing new techniques, or greatly improving on previous techniques, which makes comparing and evaluating the techniques difficult to do. A technique previously considered inadequate may have been improved upon outside of its use in translation, and might no longer be inadequate. The methods used are factors which contribute to the process of translation and need to be considered in an evaluation of optimising translation systems. This project aims to look into the field of sign language translation in terms of notation systems; what systems exists, what data is currently available, and which of them might be best suited for machine translation purposes. The question being asked is how using a textual representation of signs could aid machine translation, and which notation would best suit the task. To do this, the research will provide an analysis of the major notation systems and some minor ones with a focus on their suitability for translation by machine. This research will be both theoretical and practical, involving the building of a basic translation system from available data in order to practically test the limitations and strengths of that notation. The result of this research will hopefully provide knowledge that can be built upon to improve future translation systems. To begin with, a background into the three main fields will be provided; sign language lin- guistics, machine translation, and the combination: machine translation of sign languages. A brief overview of previous translation systems that have been built or prototyped will be provided. The research will then provide an analysis of notation systems and go into describing the process of constructing a corpus for translation, with reference to practical experience translating ASL data with the Moses translation system. Chapter 2 Background 2.1 Sign Language Sign languages have not been studied as extensively as spoken languages, and the field of research is still fairly young [13]. A good understanding of how sign languages are used is necessary for creating a good translation system. Sign languages are vastly different from spoken languages; some of the methods used in spoken language translation/recognition systems can be applied, but not all of them are suitable. Sign languages are not all the same; each one will have differences in syntax, lexicon, etc. However, there are concepts referring to the nature of the production of signs that are unique to sign languages and that apply to all sign languages. What is known about sign language universals must be considered and used to adapt translation systems. 2.1.1 3D Signing Space Sign languages exist in a visual medium and are three dimensional; spoken languages exist in an audio medium and are two dimensional. Sign languages function within both space and time, therefore requiring specific techniques for processing, and posing interesting challenges not encountered in the translation/recognition of spoken languages. A signer will use their whole body and the space around them in communication. The hands of a signer are the main production units of signs, but anywhere from above the head to about waist height on the body is used as place of articulation[8].
Loading...
Loading...
Loading...
Loading...
Loading...

36 pages remaining, click to load more.

Recommended publications
  • An Animated Avatar to Interpret Signwriting Transcription
    An Animated Avatar to Interpret SignWriting Transcription Yosra Bouzid Mohamed Jemni Research Laboratory of Technologies of Information and Research Laboratory of Technologies of Information and Communication & Electrical Engineering (LaTICE) Communication & Electrical Engineering (LaTICE) ESSTT, University of Tunis ESSTT, University of Tunis yosrabouzid@hotmail.fr Mohamed.jemni@fst.rnu.tn Abstract—People with hearing disability often face multiple To address this issue, different methods and technologies barriers when attempting to interact with hearing society. geared towards deaf communication have been suggested over The lower proficiency in reading, writing and understanding the the last decades. For instance, the use of sign language spoken language may be one of the most important reasons. interpreters is one of the most common ways to ensure a Certainly, if there were a commonly accepted notation system for successful communication between deaf and hearing persons in sign languages, signed information could be provided in written direct interaction. But according to a WFD survey in 2009, 13 form, but such a system does not exist yet. SignWriting seems at countries out of 93 do not have any sign language interpreters, present the best solution to the problem of SL representation as it and in many of those countries where there are interpreters, was intended as a practical writing system for everyday there are serious problems in finding qualified candidates. communication, but requires mastery of a set of conventions The digital technologies, particularly video and avatar-based different from those of the other transcriptions systems to become a proficient reader or writer. To provide additional systems, contribute, in turn, in bridging the communication support for deaf signers to learn and use such notation, we gap.
    [Show full text]
  • A Human-Editable Sign Language Representation for Software Editing—And a Writing System?
    A human-editable Sign Language representation for software editing—and a writing system? Michael Filhol michael.filhol@limsi.fr LIMSI, CNRS, Université Paris Saclay Orsay, France Abstract To equip SL with software properly, we need an input system to rep- resent and manipulate signed contents in the same way that every day software allows to process written text. Refuting the claim that video is good enough a medium to serve the purpose, we propose to build a repres- entation that is: editable, queryable, synthesisable and user-friendly—we define those terms upfront. The issue being functionally and conceptually linked to that of writing, we study existing writing systems, namely those in use for vocal languages, those designed and proposed for SLs, and more spontaneous ways in which SL users put their language in writing. Ob- serving each paradigm in turn, we move on to propose a new approach to satisfy our goals of integration in software. We finally open the prospect of our proposition being used outside of this restricted scope, as a writing system in itself, and compare its properties to the other writing systems presented. 1 Motivation and goals The main motivation here is to equip Sign Language (SL) with software and foster implementation as available tools for SL are paradoxically limited in such digital times. For example, translation assisting software would help respond arXiv:1811.01786v1 [cs.CL] 5 Nov 2018 to the high demand for accessible content and information. But equivalent text-to-text software relies on source and target written forms to work, whereas similar SL support seems impossible without major revision of the typical user interface.
    [Show full text]
  • Greek Alphabet ( ) Ελληνικ¿ Γρ¿Μματα
    Greek alphabet and pronunciation 9/27/05 12:01 AM Writing systems: abjads | alphabets | syllabic alphabets | syllabaries | complex scripts undeciphered scripts | alternative scripts | your con-scripts | A-Z index Greek alphabet (ελληνικ¿ γρ¿μματα) Origin The Greek alphabet has been in continuous use for the past 2,750 years or so since about 750 BC. It was developed from the Canaanite/Phoenician alphabet and the order and names of the letters are derived from Phoenician. The original Canaanite meanings of the letter names was lost when the alphabet was adapted for Greek. For example, alpha comes for the Canaanite aleph (ox) and beta from beth (house). At first, there were a number of different versions of the alphabet used in various different Greek cities. These local alphabets, known as epichoric, can be divided into three groups: green, blue and red. The blue group developed into the modern Greek alphabet, while the red group developed into the Etruscan alphabet, other alphabets of ancient Italy and eventually the Latin alphabet. By the early 4th century BC, the epichoric alphabets were replaced by the eastern Ionic alphabet. The capital letters of the modern Greek alphabet are almost identical to those of the Ionic alphabet. The minuscule or lower case letters first appeared sometime after 800 AD and developed from the Byzantine minuscule script, which developed from cursive writing. Notable features Originally written horizontal lines either from right to left or alternating from right to left and left to right (boustophedon). Around 500 BC the direction of writing changed to horizontal lines running from left to right.
    [Show full text]
  • Expanding Information Access Through Data-Driven Design
    ©Copyright 2018 Danielle Bragg Expanding Information Access through Data-Driven Design Danielle Bragg A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2018 Reading Committee: Richard Ladner, Chair Alan Borning Katharina Reinecke Program Authorized to Offer Degree: Computer Science & Engineering University of Washington Abstract Expanding Information Access through Data-Driven Design Danielle Bragg Chair of the Supervisory Committee: Professor Richard Ladner Computer Science & Engineering Computer scientists have made progress on many problems in information access: curating large datasets, developing machine learning and computer vision, building extensive networks, and designing powerful interfaces and graphics. However, we sometimes fail to fully leverage these modern techniques, especially when building systems inclusive of people with disabilities (who total a billion worldwide [168], and nearly one in five in the U.S. [26]). For example, visual graphics and small text may exclude people with visual impairments, and text-based resources like search engines and text editors may not fully support people using unwritten sign languages. In this dissertation, I argue that if we are willing to break with traditional modes of information access, we can leverage modern computing and design techniques from computer graphics, crowdsourcing, topic modeling, and participatory design to greatly improve and enrich access. This dissertation demonstrates this potential
    [Show full text]
  • Complete Issue
    _____________________________________________________________ Volume 8 October 1993 Number 2 _____________________________________________________________ Editor Editorial Assistants John Miles Foley Dave Henderson Elizabeth P. McNulty Catherine S. Quick Slavica Publishers, Inc. For a complete catalog of books from Slavica, with prices and ordering information, write to: Slavica Publishers, Inc. P.O. Box 14388 Columbus, Ohio 43214 ISSN: 0883-5365 Each contribution copyright (c) 1993 by its author. All rights reserved. The editor and the publisher assume no responsibility for statements of fact or opinion by the authors. Oral Tradition seeks to provide a comparative and interdisciplinary focus for studies in oral literature and related fields by publishing research and scholarship on the creation, transmission, and interpretation of all forms of oral traditional expression. As well as essays treating certifiably oral traditions, OT presents investigations of the relationships between oral and written traditions, as well as brief accounts of important fieldwork, a Symposium section (in which scholars may reply at some length to prior essays), review articles, occasional transcriptions and translations of oral texts, a digest of work in progress, and a regular column for notices of conferences and other matters of interest. In addition, occasional issues will include an ongoing annotated bibliography of relevant research and the annual Albert Lord and Milman Parry Lectures on Oral Tradition. OT welcomes contributions on all oral literatures, on all literatures directly influenced by oral traditions, and on non-literary oral traditions. Submissions must follow the list-of reference format (style sheet available on request) and must be accompanied by a stamped, self-addressed envelope for return or for mailing of proofs; all quotations of primary materials must be made in the original language(s) with following English translations.
    [Show full text]
  • Hwaslpreview.Pdf
    How to Write American Sign Language by Adrean Clark For all generations of signers. May the past be preserved and the future built. How to Write American Sign Language Copyright © 2012 by Adrean Clark. Published by ASLwrite in Burnsville, Minnesota. Si5s concept by Robert Arnold. Photographs by Julia Dameron and Erik Call. Models (in order of appearance): Julia Dameron, Montrell White, and Amber Zion. ISBN-13: 978-0-9858768-0-7 Library of Congress Control Number: 2012912030 All rights reserved. Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of both the copyright owner and the above publisher of this book. t Table of Contents Acknowledgments . 4 Introduction . 5 Chapter One: The Digibet . 6 Chapter Two: Diacritics . 19 Chapter Three: Movement Marks . 29 Chapter Four: Locatives . 43 Chapter Five: Extramanual Marks . 53 Chapter Six: Indicators . 63 Chapter Seven: Composition . 73 Resources . 87 Answer Key . 94 a Acknowledgments This book would not be possible without the vision of Robert Arnold (si5s.org). His hours spent tutoring me and our time working together on developing this amazing language are much appreciated. He also had valuable input on the contents of this book. I could not have become fluent without the help of Julia Dameron (juliadameron.com), who was instrumental in creating the early American Sign Language Writing Dictionary. Our days writing pushed the boundaries of the written language.
    [Show full text]
  • Signwriting Symbols to Students
    JTC1/SC2/WG2 N4342 L2/12-321 2012-10-14 Universal Multiple-Octet Coded Character Set International Organization for Standardization Organisation Internationale de Normalisation Международная организация по стандартизации Doc Type: Working Group Document Title: Proposal for encoding Sutton SignWriting in the UCS Source: Michael Everson, Martin Hosken, Stephen Slevinski, and Valerie Sutton Status: Individual Contribution Action: For consideration by JTC1/SC2/WG2 and UTC Date: 2012-10-14 Replaces: N4015 1. Introduction. SignWriting is a script developed in 1974 by Valerie Sutton, the inventor of Sutton Movement Writing, who two years earlier had developed DanceWriting. SignWriting is a featural script, its glyphs being visually iconic as well as in their spatial arrangement in text, which represents a sort of snapshot of any given sign. SignWriting is currently being used to write the following Sign Languages: American Sign Language (in USA, English-speaking Canada) Japanese Sign Language Arabian Sign Languages Malawi Sign Language Australian Sign Language Malaysian Sign Language Bolivian Sign Language Maltese Sign Language Brazilian Sign Language Mexican Sign Language British Sign Language Nepalese Sign Language Catalan Sign Language New Zealand Sign Language Colombian Sign Language Nicaraguan Sign Language Czech Sign Language Norwegian Sign Language Danish Sign Language Peruvian Sign Language Dutch Sign Language Philippines Sign Language Ethiopian Sign Language Polish Sign Language Finnish Sign Language Portugese Sign Language Flemish Sign Language Québec Sign Language French-Belgian Sign Language South African Sign Language French Sign Language Spanish Sign Language German Sign Language Swedish Sign Language Greek Sign Language Swiss Sign Language Irish Sign Language Taiwanese Sign Language Italian Sign Language Tunisian Sign Language A variety of literature exists in SignWriting.
    [Show full text]
  • A Cross-Linguistic Guide to Signwriting ® a Phonetic Approach
    A Cross-Linguistic ® Guide to SignWriting A phonetic approach Stephen Parkhurst Dianne Parkhurst A Cross-Linguistic Guide to SignWriting ®: A phonetic approach ©2008 Stephen Parkhurst Revision 2010 For use at SIL-UND courses during the summer of 2010. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, transmitted or utilized in any form or by any means, electronic, mechanical, photocopying, recorded or otherwise, without permission from the authors. Stephen and Dianne Parkhurst E-mail: steve-dianne_parkhurst@sil.org A note from the authors SignWriting®, also known as Sutton Movement Writing for Sign Language, was invented by Valerie Sutton in 1974. Over the years the system has changed significantly and has gradually grown in acceptance and popularity in more than 30 countries. While there are other writing systems and notation systems for writing signed languages, we have not found any system that is as useful for writing accurately any sign or movement (including all non-manual movements and expressions) with relative ease and speed. It is also the only writing system that we have tried that is possible to read faster than one can physically produce the signs (outpacing even photos and line drawings in ease and speed of reading). We have taken much of the material for this manual from a course we developed for teaching SignWriting (SW) to Deaf adults in Spain. That course in Spain focused on teaching the symbols of SW that are used in Spanish Sign Language (or LSE, for Lengua de Signos Española) with a heavy focus on reading.
    [Show full text]
  • 22Hwaslebookfree.Pdf
    How to Write American Sign Language by Adrean Clark For all generations of signers. May the past be preserved and the future built. How to Write American Sign Language Copyright © 2012 by Adrean Clark. Published by ASLwrite in Burnsville, Minnesota. www.aslwrite.com Si5s concept by Robert Arnold. Photographs by Julia Dameron and Erik Call. Models (in order of appearance): Julia Dameron, Montrell White, and Amber Zion. ISBN-13: 978-0-9858768-1-4 All rights reserved. Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of both the copyright owner and the above publisher of this book. t Table of Contents Acknowledgments . 4 Introduction . 5 Chapter One: The Digibet . 6 Chapter Two: Diacritics . 19 Chapter Three: Movement Marks . 29 Chapter Four: Locatives . 43 Chapter Five: Extramanual Marks . 53 Chapter Six: Indicators . 63 Chapter Seven: Composition . 73 Resources . 87 Answer Key . 94 Author’s Note: This is a special ebook for free community and educational use. Please check the ASLwrite website for updated content -- and if you come up with something new that benefits written ASL, please do let me know at adrean@aslwrite.com! a Acknowledgments This book would not be possible without the vision of Robert Arnold (si5s.org). His hours spent tutoring me and our time working together on developing this amazing language are much appreciated. He also had valuable input on the contents of this book.
    [Show full text]
  • Automated Sign Language Translation: the Role of Artificial Intelligence Now and in the Future
    Automated Sign Language Translation: The Role of Artificial Intelligence Now and in the Future Lea Baumgartner,¨ Stephanie Jauss, Johannes Maucher and Gottfried Zimmermann Hochschule der Medien, Nobelstraße 10, 70569 Stuttgart, Germany Keywords: Sign Language Translation, Sign Language Recognition, Sign Language Generation, Artificial Intelligence. Abstract: Sign languages are the primary language of many people worldwide. To overcome communication barriers between the Deaf and the hearing community, artificial intelligence technologies have been employed, aiming to develop systems for automated sign language recognition and generation. Particularities of sign languages have to be considered - though sharing some characteristics of spoken languages - since they differ in others. After providing the linguistic foundations, this paper gives an overview of state-of-the-art machine learning approaches to develop sign language translation systems and outlines the challenges in this area that have yet to be overcome. Obstacles do not only include technological issues but also interdisciplinary considerations of development, evaluation and adoption of such technologies. Finally, opportunities and future visions of automated sign language translation systems are discussed. 1 INTRODUCTION There are, however, differences in how sign lan- guages work in detail, some of which are mentioned A basic understanding of the particularities and no- using the example of American Sign Language (ASL) tation of sign language serves to better understand in the following. Since suffixes to verbs like in spoken the importance and challenges of automated sign lan- languages are not possible, ASL tenses are built by guage translation. We use both the terms deaf and adding words in the beginning or at the end of a sen- Deaf throughout this paper, the first referring solely tence.
    [Show full text]
  • © 2013 Gabrielle Anastasia Jones
    © 2013 Gabrielle Anastasia Jones A CROSS-CULTURAL AND CROSS-LINGUISTIC ANALYSIS OF DEAF READING PRACTICES IN CHINA: CASE STUDIES USING TEACHER INTERVIEWS AND CLASSROOM OBSERVATIONS BY GABRIELLE ANASTASIA JONES DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Educational Psychology in the Graduate College of the University of Illinois at Urbana-Champaign, 2013 Urbana, Illinois Doctoral Committee: Associate Professor Kiel Christianson, Chair Professor Jenny Singleton, Director of Research, Georgia Institute of Technology Professor Jerome Packard Professor Richard C. Anderson Professor Donna Mertens, Gallaudet University Abstract Longstanding beliefs about how children read accentuate the importance of phonological processing in mapping letters to sound. However, when one considers the nature of the script being read, the process can be far more complicated, particularly in the case of an alphabetic script like English (Share, 2008). Cross-cultural reading research reveals alternative modes of processing text that is not entirely phonological. Chinese is known for its non-alphabetic script and its greater reliance upon morphological processing (Anderson & Kuo, 2006), visual skills (Ho & Bryant, 1997; Huang & Hanley, 1995; McBride-Chang & Zhong, 2003), and radical awareness- all argued to be essential skills in deciphering the character-based script. Given the more visual and semantic structure of Chinese, would reading Chinese be easier for deaf students than a sound-based system like English? Deaf readers in China are nevertheless required to learn two very different scripts- one alphabetic (Pinyin) and another non-alphabetic (Simplified Chinese characters). Furthermore, we must consider the relationship between languages in the child’s environment (e.g.
    [Show full text]
  • Writing Signed Languages: What For? What Form? Donald A
    Writing Signed Languages: What For? What Form? Donald A. Grushkin American Annals of the Deaf, Volume 161, Number 5, Winter 2017, pp. 509-527 (Article) Published by Gallaudet University Press DOI: https://doi.org/10.1353/aad.2017.0001 For additional information about this article https://muse.jhu.edu/article/648961 Access provided by University of Connecticut @ Storrs (9 Jun 2017 21:07 GMT) 18991-AAD161.5_Winter2017 2/9/17 2:54 PM Page 509 Grushkin, D. A. (2017). Writing signed languages: What for? What form? American Annals of the Deaf, 161 (5), 509–527. WRITING SIGNED LANGUAGES : W HAT FOR ? WHAT FORM ? IGNED LANGUAGES around the world have tended to maintain an “oral,” unwritten status. Despite the advantages of possessing a written form of their language, signed language communities typically resist and reject attempts to create such written forms. The present article ad - dresses many of the arguments against written forms of signed lan - guages, and presents the potential advantages of writing signed languages. Following a history of the development of writing in spoken as well as signed language populations, the effects of orthographic types upon literacy and biliteracy are explored. Attempts at writing signed lan - guages have followed two primary paths: “alphabetic” and “icono - graphic.” It is argued that for greatest congruency and ease in developing biliteracy strategies in societies where an alphabetic script is used for the spoken language, signed language communities within Sthese societies are best served by adoption of an alphabetic script for DONALD A. G RUSHKIN writing their signed language. Keywords: writing, written signed the development of a conventionally GRUSHKIN IS A PROFESSOR , D EAF STUDIES languages, biliteracy, Deaf education, accepted written system for signed lan - PROGRAM , C ALIFORNIA STATE UNIVERSITY , orthography guages has yet to take place.
    [Show full text]