UAIS 2023 : International Journal on Universal Access in the Information Society
Call For Papers
Special Issue on Sign Language Translation and Avatar Technologies
Aims and scope of this special issue
Many people are surprised to find that the primary communication barrier for the Deaf is not sound, but language. Members of a Deaf community use a signed language as their preferred language. These signed languages are natural languages, as fully formed as any spoken language and are independent of the languages used by a region’s hearing communities. Like spoken languages, signed languages vary from one geographic region to another.
Due to the barriers imposed by language, access to education, employment and health care are a daily challenge to members of the Deaf communities. Beyond situations where qualified human interpreters are indispensable, they need efficient, affordable translation in order to gain access to services that are taken for granted in the hearing world. For this reason, automatic translation between spoken and signed languages promises substantial benefits to Deaf communities.
Progress toward automatic spoken/signed language translation has been slower than progress in spoken/spoken language translation due in part to the additional challenges posed by signed/spoken translation. These include differences in modality (gestural/visual vs. oral/aural), the lack of a standard written form, and the scarcity of resources for recognition, analysis, and display. Recent advances in virtual character technology and enhanced recognition techniques have begun to make inroads into meeting these challenges. We invite papers on three main topics: translation of sign language, animation of sign language using avatars, and usability evaluation of practical translation and animation systems. We welcome theoretical, methodological, and empirical research, of both a technological and non-technological nature.
Topics of specific interest
Important aspects and topics to be discussed evolve around (but are not limited to):
● Rule-based and data-driven translation Strengths, challenges, comparison of results.
● Innovations in recognition techniques: from the visual to the linguistic Identification and segmentation of sign language from various media sources.
● Mapping techniques between linguistic annotation and visual display - representation at the phonetic, phonemic, morphological, syntactic, and prosodic levels.
● Integration of automated and manual techniques of annotation.
● User-centered design and evaluation. Case studies of user involvement. Innovations in user evaluation techniques.
Submissions should be prepared according to the author instructions available at the journal homepage, http://www.springer.com/computer/hci/journal/10209 . A typical length for a long paper is between 20 and 30 pages. Please also note that 20-30 pages of unformatted ordinary MS Word text would typically result in a shorter document of 12-20 pages, formatted according to the Springer guidelines.
For Invited papers presented at conference sessions, the updated journal submission must significantly extend the original one, comprising at least 60% new and previously unpublished material.
Initial manuscripts must be submitted electronically in the form of PDF file through the Springer Editorial Management System available at https://www.editorialmanager.com/uais/default.aspx . During the submission process, clearly indicate in your cover letter that the paper is submitted for the Special Issue on Sign Language Translation and Avatar Technologies..
All papers will be peer reviewed by three reviewers, experts in the field, appointed by the Guest Editor of the issue in consultation with the Editor-in-Chief of the Journal. Please note that UAIS follows a single-blinded review process, therefore there is no need to anonymize the submissions.
Submission of an article implies that:
- The work described has not been published before, except in form of an abstract or as part of a published lecture, conference, review, or thesis.
- It is not under consideration for publication elsewhere.
For further information, please, refer to the "Copyright information" section on the Website of the UAIS Journal.
Annelies Braffort Université Paris-Saclay France, email@example.com
Eleni Efthimiou Institute for Speech and Language Processing, Greece firstname.lastname@example.org
Thomas Hanke University of Hamburg, Germany, email@example.com
Dimitar Shterionov Tilburg University, The Netherlands, firstname.lastname@example.org
Rosalee Wolfe Institute for Speech and Language Processing, Greece, Rosalee.Wolfe@athenarc.gr