What Corpus-Based Research on Negation in Auslan and PJM Tells Us About Building and Using Sign Language Corpora
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Learn to Use Signpuddle 1.0 on The
Some Dictionaries: ™ SignPuddle Online American Sign Language www.SignBank.org/signpuddle Arabic Sign Languages Brazilian Sign Language British Sign Language Colombian Sign Language Czech Sign Language Danish Sign Language Finnish Sign Language Flemish Sign Language French Sign Language German Sign Language Greek Sign Language International Sign Languages Irish Sign Language Italian Sign Language Japanese Sign Language Maltese Sign Language Come Splash in a Sign Puddle! Netherlands Sign Language 1. FREE on the web! Nicaraguan Sign Language Northern Ireland Sign Language 2. Search Sign Language Dictionaries. Norwegian Sign Language 3. Create your own signs and add them. Polish Sign Language 4. Send email in SignWriting®. Quebec Sign Language 5. Translate words to SignWriting. Spanish Sign Language 6. Create documents with SignWriting. Swiss Sign Languages 7. Have fun sharing signs on the internet! Taiwan Sign Language ...and others... http://www.SignBank.org/signpuddle Search by Words 1. Click on the icon: Search by Words 2. In the Search field: Type a word or a letter. 3. Press the Search button. 4. All the signs that use that word will list for you in SignWriting. 5. You can then copy the sign, or drag and drop it, into other documents. http://www.SignBank.org/signpuddle Search by Signs 1. Click on the icon: Search by Signs 2. In the Search field: Type a word or a letter. 3. Press the Search button. 4. The signs will list in small size. 5. Click on the small sign you want, and a larger version will appear... http://www.SignBank.org/signpuddle Search by Symbols 1. -
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. -
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. -
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]. -
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). -
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. -
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. -
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 ......... -
IFHOHYP Newsletter 1/2007
IFHOHYP NEWS Summer 2007 The International Federation of Hard of Hearing Young People Magazine New Trends in Educating Hearing Impaired People by Svetoslava Saeva (Bulgaria) In the period 21-25 March 2007 an International Contact Seminar New Trends in Educating Hearing Impaired People was held for the first time in Bratislava, Slovakia (http://akademia.exs.sk). The seminar is realized as a main activity of a project of the European Culture Society, Bratislava and is financially supported by: Youth Programme – Action 5, Open Society Fund and Austrian Culture Forum. All activities were interpreted into English, Slovak, Slovak Sign language and International Sign. The seminar was under the auspices of Mr. Dušan Čaplovič – Deputy Prime Minister of the Government of Slovakia for Knowledge-Based Society, European Affairs, Human Rights and Minorities and Mrs. Viera Tomanová – Minister of Labour, Social Affairs and Family in Slovakia. The seminar was divided into two main parts concerning activities in the whole period. Svetoslava (in the right) The first part was on 22 March when Open Public Seminar was realized in the capital of Slovakia – Bratislava. There were more than 110 people from different countries that took part in the seminar. Many of the participants were hearing impaired. There were many interesting presentations about technologies and innovations in education and preparation for universities as well as for the labour market of hearing impaired and deaf people. Mr. Andrej Buday – a Slovak project manager and president of the Association of Driving Schools in Slovak Republic shared very valuable experience about teaching deaf and hearing impaired people how to drive correctly and safely. -
Stakeholders' Views on Use of Sign Language Alone As a Medium Of
INTERNATIONAL JOURNAL OF SPECIAL EDUCATION Vol.33, No.1, 2018 Stakeholders’ Views on Use of Sign Language Alone as a Medium of Instruction for the Hearing Impaired in Zambian Primary Schools Mandyata Joseph, Kamukwamba Kapansa Lizzie, School of Education, University of Zambia ([email protected]) Abstract The study examined views of stakeholders on the use of Sign Language as a medium of instruction in the learning of hearing impaired in primary schools of Lusaka, Zambia. A case study design supported by qualitative methods was used. The sample size was 57, consisting of teachers, pupils, curriculum specialist, education standards officers, lecturers and advocators on the rights of persons with disabilities. Purposive sampling techniques to selected the sample, interview and focused group discussion guides were tools for data collection. The study revealed significant differences in views of stakeholders on use of Sign Language alone as medium of instruction. While most participants felt sign language alone was ideal for learning, others believed learners needed exposure to total communication (combination of oral and sign language) to learn better. Those who felt using sign language alone was better, believed the practice had more positive effects on learning and that use of oral language, total communication often led to confusion in classroom communication among learners with hearing impairments. Participants who opposed use of sign language alone were of the view teachers: were ill-prepared; signs were limited in scope; education system lacked instructional language policy and learning environment were inappropriate to support use of sign language alone in the learning process. The study recommended strengthening of training of sign language teachers and introduction of sign language as an academic subject before it can be used as the sole medium of classroom instruction in the Zambian primary schools. -
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 ................................................................ -
Marcin Mizak Sign Language – a Real and Natural Language
LUBELSKIE MATERIAŁY NEOFILOLOGICZNE NR 35, 2011 Marcin Mizak Sign Language – A Real and Natural Language 1. Introduction It seems reasonable to begin a discussion on the “realness” and “naturalness” of sign language by comparing it to other human languages of whose “real” and “natural” status there can be no doubt whatsoever. They will be our reference point in the process of establishing the status of sign language. The assumption being made in this paper is that all real and natural languages share certain characteristics with one another, that they all behave in a certain way and that certain things happen to all of them. If it transpires that the same characteristics and behaviours are also shared by sign language and that whatever happens to real and natural languages also happens to sign language then the inevitable conclusion follows: sign language is indeed a real and natural language 1. 2. The number of languages in the world One of the first things to be noticed about real and natural languages is their great number. Ethnologue: Languages of the World , one of the most reliable and comprehensive encyclopedic reference publications, catalogues in its 16 th edition of 2009 6,909 known living languages in 1 The designation “sign language,” as used in this article, refers to the languages used within communities of the deaf. American Sign Language, for example, is a sign language in this sense. Artificially devised systems, such as Signed English, or Manual English, are not sign languages in this sense. Sign Language – A Real and Natural Language 51 the world today 2.