04608nam a22006375i 4500 978-3-031-47362-3 DE-He213 20251030113306.0 cr nn 008mamaa 241111s2024 sz | s |||| 0|eng d 9783031473623 978-3-031-47362-3 10.1007/978-3-031-47362-3 doi P306-310 CFP bicssc LAN023000 bisacsh CFP thema Sign Language Machine Translation [electronic resource] / edited by Andy Way, Lorraine Leeson, Dimitar Shterionov. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XXI, 348 p. 74 illus., 40 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Machine Translation: Technologies and Applications, 2522-803X ; 5 Chapter 1. The Pipeline of Sign Language Machine -- Chapter 2. How it Started and How it’s Going: Sign-Language Machine Translation and Engagement with Deaf Communities over the past 25 years -- Chapter 3. The Importance of Including Signed Languages in Natural Language Processing -- Chapter 4. Sign Languages and Machine Translation: Challenges and Opportunities -- Chapter 5. Challenges with Sign Language Datasets -- Chapter 6. Language Resources for European Sign Languages.* Chapter 7. Sign languages as source language for machine translation: historical overview and challenges -- Chapter 8. Linguistic Processing for Sign Language Translation -- Chapter 9. Improving Sign Language Gloss Translation with Low-Resource Machine Translation Techniques -- Chapter 10. Sign Language Synthesis: Current Signing Avatar Systems and Representation -- Chapter 11. A Real-Time Collision Detection and Avoidance Algorithm for Fingerspelling Animation -- Chapter 12. Bridging the Gap: Understanding the Intersection of Deaf and Technical Perspectives on Signing Avatars -- Chapter 13. Sign Language Machine Translation Communication and Engagement. Chapter 14. (Towards) Sign Language Machine Translation in Practice. This book, for the first time, collects important current topics in the area of sign language translation in a single volume. The topic is introduced more generally to benefit newcomers to the field before diving into the current state-of-the-art methods of Sign Language Machine Translation (SLMT), together with an in-depth description of issues specific to this topic, including: an introduction to and historical overview of SLMT; ethical issues related to the engagement of and with deaf users; the importance of data; the sign languages of Europe; sign language recognition and synthesis, including via avatars; data-driven and linguistically-informed models of SLMT; gloss translation; fingerspelling; SLMT communication; and SLMT in practice. Of interest to MT developers and users as well as people working in deaf studies, this volume presents cutting-edge research on machine translation in the field of deaf studies. Translating and interpreting. 70428 Machine learning. 55059 Applied linguistics. People with disabilities Education. 67591 Signal processing. Inclusive education. 59665 Language Translation. 70430 Machine Learning. 55059 Applied Linguistics. Education and Disability. 67592 Signal, Speech and Image Processing. Inclusive Education. 59665 Way, Andy. editor. edt http://id.loc.gov/vocabulary/relators/edt 87306 Leeson, Lorraine. editor. edt http://id.loc.gov/vocabulary/relators/edt 87307 Shterionov, Dimitar. editor. edt http://id.loc.gov/vocabulary/relators/edt 87308 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031473616 Printed edition: 9783031473630 Printed edition: 9783031473647 Machine Translation: Technologies and Applications, 2522-803X ; 5 87309 https://doi.org/10.1007/978-3-031-47362-3 ZDB-2-EDA ZDB-2-SXED 64856 64856