This paper identifies some common and specific pitfalls in the development of sign language technologies targeted at deaf communities, with a specific focus on signing avatars. It makes the call to urgently interrogate some of the ideologies behind those technologies, including issues of ethical and responsible development. The paper addresses four separate and interlinked issues: ideologies about deaf people and mediated communication, bias in data sets and learning, user feedback, and applications of the technologies. The paper ends with several take away points for both technology developers and deaf NGOs. Technology developers should give more consideration to diversifying their team and working interdisciplinary, and be mindful of the biases that inevitably creep into data sets. There should also be a consideration of the technologies’ end users. Sign language interpreters are not the end users nor should they be seen as the benchmark for language use. Technology developers and deaf NGOs can engage in a dialogue about how to prioritize application domains and prioritize within application domains. Finally, deaf NGOs policy statements will need to take a longer view, and use avatars to think of a significantly better system compared to what sign language interpreting services can provide.
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Growing research in sign language recognition, generation, and translation AI has been accompanied by calls for ethical development of such technologies. While these works are crucial to helping individual researchers do better, there is a notable lack of discussion of systemic biases or analysis of rhetoric that shape the research questions and methods in the field, especially as it remains dominated by hearing non-signing researchers. Therefore, we conduct a systematic review of 101 recent papers in sign language AI. Our analysis identifies significant biases in the current state of sign language AI research, including an overfocus on addressing perceived communication barriers, a lack of use of representative datasets, use of annotations lacking linguistic foundations, and development of methods that build on flawed models. We take the position that the field lacks meaningful input from Deaf stakeholders, and is instead driven by what decisions are the most convenient or perceived as important to hearing researchers. We end with a call to action: the field must make space for Deaf researchers to lead the conversation in sign language AI.
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This research report contains the findings of an international study consisting of three online ‘living’ surveys. The surveys focused on how the COVID-19 pandemic has impacted sign language interpreters’ working practices, how this was experienced by them, and how digital disruption caused by the pandemic is impacting and innovating the sign language interpreting profession. The study was carried out between April 2020 and July 2020; the largest contingent of respondents over all three surveys were from the U.S., followed by the UK, the Netherlands, Germany, Finland and Belgium. Respondents commented that the crisis will probably accelerate the need for remote interpreting training in interpreter training programs. Another resurfacing issue was the perceived need for sign language interpreting students to have face-to-face practice and live mentoring. Respondents commented on what benefits they thought remote interpreting might bring to the table, both for themselves and for deaf people. In general, the most significant benefits that were mentioned were flexibility and the possibility to improve efficiency and availability of sign language interpreting services. Notwithstanding these benefits, a significant number of respondents claimed that remote interpreting is more stressful than face-to-face interpreting and requires a heavier cognitive load.
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In this paper we describe our work in progress on the development of a set of criteria to predict text difficulty in Sign Language of the Netherlands (NGT). These texts are used in a four year bachelor program, which is being brought in line with the Common European Framework of Reference for Languages (Council of Europe, 2001). Production and interaction proficiency are assessed through the NGT Functional Assessment instrument, adapted from the Sign Language Proficiency Interview (Caccamise & Samar, 2009). With this test we were able to determine that after one year of NGT-study students produce NGT at CEFR-level A2, after two years they sign at level B1, and after four years they are proficient in NGT on CEFR-level B2. As a result of that we were able to identify NGT texts that were matched to the level of students at certain stages in their studies with a CEFR-level. These texts were then analysed for sign familiarity, morpheme-sign rate, use of space and use of non-manual signals. All of these elements appear to be relevant for the determination of a good alignment between the difficulty of NGT signed texts and the targeted CEFR level, although only the morpheme-sign rate appears to be a decisive indicator
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This article examines the impact of the COVID-19 pandemic on the sign language interpreting profession drawing on data from a fourth and final survey conducted in June 2021 as part of a series of online “living surveys” during the pandemic. The survey, featuring 331 respondents, highlights significant changes in the occupational conditions and practices of sign language interpreters due to the sudden shift towards remote video-mediated interpreting. The findings reveal a range of challenges faced by interpreters, including the complexities of audience design, lack of backchanneling from deaf consumers, the need for heightened self-monitoring, nuanced conversation management, and team work. Moreover, the study highlights the physical and mental health concerns that have emerged among interpreters as a result of the shift in working conditions, and a need for interpreters to acquire new skills such as coping with the multimodal nature of online interpreting. While the blend of remote, hybrid, and on-site work has introduced certain advantages, it also poses new challenges encompassing workload management, online etiquette, and occupational health concerns. The survey’s findings underscore the resilience and adaptability of SLIs in navigating the shift to remote interpreting, suggesting a lasting transformation in the profession with implications for future practice, training, and research in the post-pandemic era.
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The following guidelines address issues related specifically to sign language tests and testing of children since most of the existing guidelines focus on tests for adult learners. Links are provided to existing guidelines for test development, such as from the International Testing Commission (ITC), or the European Association of Language Testing and Assessment (EALTA), which include more general, construct-independent issues on (language) tests to provide additional/in-depth information. The guidelines stated here serve as a point of reference to develop, evaluate, and use tests, both for children or adult learners of a sign language. To investigate specific topics more in-depth, we recommend using existing guidelines (see Additional resources and guidelines for (language) test development) or refer to publications on sign language test development and adaptation (see Selected references
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Communication between healthcare professionals and deaf patients has been particularly challenging during the COVID-19 pandemic. We have explored the possibility to automatically translate phrases that are frequently used in the diagnosis and treatment of hospital patients, in particular phrases related to COVID-19, from Dutch or English to Dutch Sign Language (NGT). The prototype system we developed displays translations either by means of pre-recorded videos featuring a deaf human signer (for a limited number of sentences) or by means of animations featuring a computer-generated signing avatar (for a larger, though still restricted number of sentences). We evaluated the comprehensibility of the signing avatar, as compared to the human signer. We found that, while individual signs are recognized correctly when signed by the avatar almost as frequently as when signed by a human, sentence comprehension rates and clarity scores for the avatar are substantially lower than for the human signer. We identify a number of concrete limitations of the JASigning avatar engine that underlies our system. Namely, the engine currently does not offer sufficient control over mouth shapes, the relative speed and intensity of signs in a sentence (prosody), and transitions between signs. These limitations need to be overcome in future work for the engine to become usable in practice.
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Abstract van prestentatie. According to Roy and Napier (2015), the earliest research on sign language interpreting dates to the mid-1970s. More recently we have acknowledged the need for research to be part of sign language interpreter (SLI) education programs (Winston, 2013). At present, educators feel an urgent need to embed research in their SLI programs with two goals: first, to firmly base their teaching in evidencebased practice, and second, to teach future interpreters how to continuously improve their practice
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We present a number of methodological recommendations concerning the online evaluation of avatars for text-to-sign translation, focusing on the structure, format and length of the questionnaire, as well as methods for eliciting and faithfully transcribing responses.
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De African Digital Rights Network (ADRN) heeft een nieuw rapport gepubliceerd waarin de toevoer en verspreiding van digitale surveillance technologie in Afrika in kaart is gebracht. Onderzoeker Anand Sheombar van het lectoraat Procesinnovatie & Informatiesystemen is betrokken bij het ADRN-collectief en heeft samen met de Engelse journalist Sebastian Klovig Skelton, door middel van desk research de aanvoerlijnen vanuit Westerse en Noordelijke landen geanalyseerd. De bevindingen zijn te lezen in dit Supply-side report hoofdstuk van het rapport. APA-bronvermelding: Klovig Skelton, S., & Sheombar, A. (2023). Mapping the supply of surveillance technologies to Africa Supply-side report. In T. Roberts (Ed.), Mapping the Supply of Surveillance Technologies to Africa: Case Studies from Nigeria, Ghana, Morocco, Malawi, and Zambia (pp. 136-167). Brighton, UK: Institute of Development Studies.
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