Templated Crisis Communication for People With Disabilities, Access and Functional Needs

Despite the Americans with Disabilities Act being more than 30 years old, many government institutions fail to fully support their constituents, and provide understandable and actionable crisis communications before, during, and after emergencies and disasters. When residents do not effectively receive, understand, and act on crisis communications in a timely manner, life safety issues can occur. People may choose not to evacuate when necessary or lack the information for properly sheltering-in-place. These and other bad decisions can be deadly. Crisis communications, as a subset of risk communications, should be aligned with all the disaster phase cycles—the before, during, and after stages of disasters and crises—so that impacted residents obtain complete information they can use. U.S. government websites, including posted crisis communications public releases, must be compliant with the Americans with Disabilities Act (ADA) under Title II and they should use templated crisis communications available in other languages, English-only audio recordings, and videos of American Sign Language.

Experiences of Sign Language Interpreters and Perspectives of Interpreting Administrators During the COVID-19 Pandemic: A Qualitative Description.

OBJECTIVE: Interpreting during the COVID-19 pandemic caused stress and adverse mental health among sign language interpreters. The objective of this study was to summarize the pandemic-related work experiences of sign language interpreters and interpreting administrators upon transitioning from on-site to remote work. METHODS: From March through August 2021, we conducted focus groups with 22 sign language interpreters in 5 settings, 1 focus group for each setting: staff, educational, community/freelance, video remote interpreting, and video relay services. We also conducted 5 individual interviews with interpreting administrators or individuals in positions of administrative leadership in each represented setting. The 22 interpreters had a mean (SD) age of 43.4 (9.8) years, 18 were female, 17 were White, all identified as hearing, and all worked a mean (SD) of 30.6 (11.6) hours per week in remote interpreting. We asked participants about the positive and negative consequences of transitioning from on-site to remote at-home interpreting. We established a thematic framework by way of qualitative description for data analysis. RESULTS: We found considerable overlap across positive and negative consequences identified by interpreters and interpreting administrators. Positive consequences of transitioning from on-site to remote-at-home interpreting were realized across 5 overarching topic areas: organizational support, new opportunities, well-being, connections/relationships, and scheduling. Negative consequences emerged across 4 overarching topic areas: technology, financial aspects, availability of the interpreter workforce, and concerns about the occupational health of interpreters. CONCLUSIONS: The positive and negative consequences shared by interpreters and interpreting administrators provide foundational knowledge upon which to create recommendations for the anticipated sustainment of some remote interpreting practice in a manner that protects and promotes occupational health.

Images as Communication of a New Normality. The Representation of the New Social Habits Introduced by the Covid19 Emergency in Public Spaces

In a constantly evolving society where radical socio-cultural changes have been introduced in the last year, as a consequence of the world health emergency linked to the spread of the Covid 19 virus, the centrality of images in the daily life of individuals has been reconfirmed. In situations of risk for the community, such as in the case of a health emergency due to the spread of a highly contagious virus, the role of communication is particularly important for public institutions, to obtain the cooperation of the population in procedures aimed at preventing the spread or slowing down the contagion, using images that describe the recommendations to be followed. The image confirms its social role in contemporary culture, as a means of communication and a channel for the rapid and direct dissemination of information, regardless of cultural level, language, or age. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Are interpreters and interpreting technology ready for the post-Covid era?

From its onset in early 2020, the Covid-19 (hereafter Covid) crisis has uncovered both the insecurity about new technologies and their flexibility. In this chapter, we will attempt to provide a non-exhaustive map of the field of interpreting technology in different settings, of research on these new technologies and research using them. Tools and resources that enhance an interpreter's performance will also be discussed as part of technological evolution, while the final question to be answered is whether "interpreters [can] survive in an AI-dominated world” (Downie 2020). This contribution wants to be a call to do more large-scale research and to inform future interpreters better about technological development and opportunities in the classroom. © 2023 John Benjamins Publishing Company.

Continuous Sign Language Interpretation to Text Using Deep Learning Models

The COVID-19 pandemic has obligated people to adopt the virtual lifestyle. Currently, the use of videoconferencing to conduct business meetings is prevalent owing to the numerous benefits it presents. However, a large number of people with speech impediment find themselves handicapped to the new normal as they cannot communicate their ideas effectively, especially in fast paced meetings. Therefore, this paper aims to introduce an enriched dataset using an action recognition method with the most common phrases translated into American Sign Language (ASL) that are routinely used in professional meetings. It further proposes a sign language detecting and classifying model employing deep learning architectures, namely, CNN and LSTM. The performances of these models are analysed by employing different performance metrics like accuracy, recall, F1- Score and Precision. CNN and LSTM models yield an accuracy of 93.75% and 96.54% respectively, after being trained with the dataset introduced in this study. Therefore, the incorporation of the LSTM model into different cloud services, virtual private networks and softwares will allow people with speech impairment to use sign language, which will automatically be translated into captions using moving camera circumstances in real time. This will in turn equip other people with the tool to understand and grasp the message that is being conveyed and easily discuss and effectuate the ideas. © 2022 IEEE.

Mobile Malaysian Sign Language Application

Due to the Covid-19 plague, children with hearing misfortune have experienced challenges in learning and practicing sign language due to need of educational services and learning assets. The next considerations for creating an educational mobile learning application to help deaf kids learn Malaysian Sign Language (MSL). The investigation was conducted through gatherings based on inquire about and interviews with subject matter experts. Instructors recommend that within the current circumstance, versatile learning application are the foremost reasonable stage for understudies to memorize or as an extra learning strategy in arrange to educate them well. This research was conducted through research-based and interview sessions with subject matter experts and followed the Multimedia Mobile Content Development (MMCD) methodology as it was shown to help accelerate development activities and ensure that the application would work and execute as planned. Once the application is developed, students from Sekolah Kebangsaan Silabukan in Lahad Datu, Sabah, will participate in beta testing. Based on the results of user acceptance tests, the application has received positive reviews from its target users. As such, the project's goals are said to have been achieved. At the conclusion of the study, the advantages, limitations and future work of Pocket Sign Language were also identified. © 2022 IEEE.

CREATION OF TERM SIGNS: TREATMENT AND TERM DESCRIPTION FOR DESCRIPTION FOR COVID-19 IN SIGN LANGUAGE

This article is about the creation of term signs in Brazilian Language Signs for the Covid-19 pandemic. The objective, therefore, was to investigate and describe the process of creating new endpoints related to the Covid-19 pandemic. For this, due to social isolation, the field of research has become virtual using platforms such as Facebook, Instagram, and WhatsApp. It is based on the morphology of Sign Language (Quadros & Karnopp, 2004). For the phonetic and morphological description, it was used Nascimento (2009) and Abreu (2019), regarding the process of creating new term signs. This analysis was focused on the study of three-term signs, the first to emerge was the one agreed in China with a mistaken conceptual reference that the disease was transmitted by bats, so it was abandoned. The second is a universalized convention that is "standard” in European and Western countries. And the third agreed in Brazil is the variant used in country © Esta obra utiliza uma licença Creative Commons CC BY: https://creativecommons.org/lice

Inaccessible media during the COVID-19 crisis intersects with the language deprivation crisis for young deaf children in the U.S

The article briefs about the language deprivation crisis for young deaf children in the U.S. With so much online and at home during the pandemic, real digital access for all children is a necessity. The legacy of U.S. media encouraging or requiring certain types of translation, while discouraging or ruling out others, matters for ideas about what does, or does not, constitute "access" to community and media for deaf children. Programming that is provided or translated into visual, fully accessible ASL and other signed languages is a key step. Rather than transcribing English into captions, it's worth looking past technologies of translation and to other countries' examples before and during COVID-19, as well as ongoing grassroots deaf organizing, to ensure that this crisis does not amplify the language deprivation crisis for deaf children in the U.S. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations

The proceedings contain 27 papers. The topics discussed include: UKP-SQUARE: an online platform for question answering research;ViLMedic: a framework for research at the intersection of vision and language in medical AI;TextPruner: a model pruning toolkit for pre-trained language models;AnnIE: an annotation platform for constructing complete open information extraction benchmark;AdapterHub playground: simple and flexible few-shot learning with adapters;QiuNiu: a Chinese lyrics generation system with passage-level input;automatic gloss dictionary for sign language learners;PromptSource: an integrated development environment and repository for natural language prompts;COVID-19 claim radar: a structured claim extraction and tracking system;TS-Anno: an annotation tool to build, annotate and evaluate text simplification corpora;and CogKGE: a knowledge graph embedding toolkit and benchmark for representing multi-source and heterogeneous knowledge.

UltrasonicGS: A Highly Robust Gesture and Sign Language Recognition Method Based on Ultrasonic Signals.

With the global spread of the novel coronavirus, avoiding human-to-human contact has become an effective way to cut off the spread of the virus. Therefore, contactless gesture recognition becomes an effective means to reduce the risk of contact infection in outbreak prevention and control. However, the recognition of everyday behavioral sign language of a certain population of deaf people presents a challenge to sensing technology. Ubiquitous acoustics offer new ideas on how to perceive everyday behavior. The advantages of a low sampling rate, slow propagation speed, and easy access to the equipment have led to the widespread use of acoustic signal-based gesture recognition sensing technology. Therefore, this paper proposed a contactless gesture and sign language behavior sensing method based on ultrasonic signals-UltrasonicGS. The method used Generative Adversarial Network (GAN)-based data augmentation techniques to expand the dataset without human intervention and improve the performance of the behavior recognition model. In addition, to solve the problem of inconsistent length and difficult alignment of input and output sequences of continuous gestures and sign language gestures, we added the Connectionist Temporal Classification (CTC) algorithm after the CRNN network. Additionally, the architecture can achieve better recognition of sign language behaviors of certain people, filling the gap of acoustic-based perception of Chinese sign language. We have conducted extensive experiments and evaluations of UltrasonicGS in a variety of real scenarios. The experimental results showed that UltrasonicGS achieved a combined recognition rate of 98.8% for 15 single gestures and an average correct recognition rate of 92.4% and 86.3% for six sets of continuous gestures and sign language gestures, respectively. As a result, our proposed method provided a low-cost and highly robust solution for avoiding human-to-human contact.

Applying Hybrid Deep Neural Network for the Recognition of Sign Language Words Used by the Deaf COVID-19 Patients.

The rapid spread of the novel corona virus disease (COVID-19) has disrupted the traditional clinical services all over the world. Hospitals and healthcare centers have taken extreme care to minimize the risk of exposure to the virus by restricting the visitors and relatives of the patients. The dramatic changes happened in the healthcare norms have made it hard for the deaf patients to communicate and receive appropriate care. This paper reports a work on automatic sign language recognition that can mitigate the communication barrier between the deaf patients and the healthcare workers in India. Since hand gestures are the most expressive components of a sign language vocabulary, a novel dataset of dynamic hand gestures for the Indian sign language (ISL) words commonly used for emergency communication by deaf COVID-19 positive patients is proposed. A hybrid model of deep convolutional long short-term memory network has been utilized for the recognition of the proposed hand gestures and achieved an average accuracy of 83.36%. The model performance has been further validated on an alternative ISL dataset as well as a benchmarking hand gesture dataset and obtained average accuracies of 97 % and 99.34 ± 0.66 % , respectively.

Towards Large Vocabulary Kazakh-Russian Sign Language Dataset: KRSL-OnlineSchool

This paper presents a new dataset for Kazakh-Russian Sign Language (KRSL) created for the purposes of Sign Language Processing. In 2020, Kazakhstan's schools were quickly switched to online mode due to COVID-19 pandemic. Every working day, the El-arna TV channel was broadcasting video lessons for grades from 1 to 11 with sign language translation. This opportunity allowed us to record a corpus with a large vocabulary and spontaneous SL interpretation. To this end, this corpus contains video recordings of Kazakhstan's online school translated to Kazakh-Russian sign language by 7 interpreters. At the moment we collected and cleaned 890 hours of video material. A custom annotation tool was created to make the process of data annotation simple and easy-to-use by Deaf community. To date, around 325 hours of videos have been annotated with glosses and 4,009 lessons out of 4,547 were transcribed with automatic speech-to-text software. KRSL-OnlineSchool dataset will be made publicly available at https://krslproject.github.io/online-school/. © European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.

Language Planning in Action: Depiction as a Driver of New Terminology in Irish Sign Language

In this paper, we examine the linguistic phenomenon known as 'depiction', which relates to the ability to visually represent semantic components (Dudis, 2004). While some elements of this have been described for Irish Sign Language, with particular attention to the 'productive lexicon' (Leeson and Grehan, 2004;Leeson and Saeed, 2012;Matthews, 1996;O'Baoill and Matthews, 2000), here, we take the analysis further, drawing on what we have learned from cognitive linguistics over the past decade. Drawing on several recently developed domain-specific glossaries (e.g., Science Technology Engineering Math1 (STEM), Covid-192, political domain, Sexual, Domestic and Gender Based Violence (SDGBV)-related vocabulary) we present ongoing analysis indicating that a deliberate focus on iconicity, in particular, elements of depiction, appears to be a primary driver. We also outline some potential implications from Deaf-led glossary development work in the context of Machine Translation goals, for example, for work in progress on the Horizon 2020 funded SignON project. © European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.

PeruSIL: A Framework to Build a Continuous Peruvian Sign Language Interpretation Dataset

Video-based datasets for Continuous Sign Language are scarce due to the challenging task of recording videos from native signers and the reduced number of people who can annotate sign language. COVID-19 has evidenced the key role of sign language interpreters in delivering nationwide health messages to deaf communities. In this paper, we present a framework for creating a multi-modal sign language interpretation dataset based on videos and we use it to create the first dataset for Peruvian Sign Language (LSP) interpretation annotated by hearing volunteers who have intermediate knowledge of PSL guided by the video audio. We rely on hearing people to produce a first version of the annotations, which should be reviewed by native signers in the future. Our contributions: i) we design a framework to annotate a sign Language dataset;ii) we release the first annotated LSP multi-modal interpretation dataset (AEC);iii) we evaluate the annotation done by hearing people by training a sign language recognition model. Our model reaches up to 80.3% of accuracy among a minimum of five classes (signs) AEC dataset, and 52.4% in a second dataset. Nevertheless, analysis by subject in the second dataset show variations worth to discuss. © European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.

Digital and Language Inequalities in Disseminating COVID-19-Related Health Campaigns in Uganda: The Effects of Confinement and Social Distancing Strategies

This article unveils existing gaps in the use of digital technologies and local languages in the context of official COVID-19 pandemic communication strategies in Uganda. It entails an analysis of a purposively drawn sample of official COVID-19 communication from the Ministry of Health through its website, notably in English and translations into few native Ugandan languages, to argue for the need for a more diverse and inclusive language strategy in pandemic containment and prevention communication strategy. Interviews were also held with a convenient sample of Ugandans from diverse ethnolinguistic and socio-demographic backgrounds to explore the way in which social distancing, a dominant strategy used in COVID-19 infection prevention control was understood by sections of the population and factors influencing their understanding, acceptance or rejection of this strategy. Discursive thematic analysis was employed to examine the ways in which important public health information and strategies aimed at controlling the spread of COVID-19 are communicated to the culturally and linguistically diverse Ugandan population. The study critically analyses the implications of the cultural interpretations and multiple meanings of strategies such as social distancing and the use of sanitizers amongst a linguistically and socio-economically diverse population. The study argues that local languages, including specialist languages such as braille and sign language play a pivotal role in spreading information and raising awareness about the current global pandemic. It highlights the need to create an inclusive, responsible and ethical mass media and internet communication and content in local Ugandan languages in addition to English which is the official language. © 2022, IFIP International Federation for Information Processing.

WordNet-Based Bulgarian Sign Language Dictionary of Crisis Management Terminology

This paper presents an online Bulgarian sign language dictionary covering terminology related to crisis management. The pressing need for such a resource became evident during the COVID pandemic when critical information regarding government measures was delivered on a regular basis to the public including Deaf citizens. The dictionary is freely available on the internet and is aimed at the Deaf, sign language interpreters, learners of sign language, social workers and the wide public. Each dictionary entry is supplied with synonyms in spoken Bulgarian, a definition, one or more signs corresponding to the concept in Bulgarian sign language, additional information about derivationally related words and similar signs with different meaning, as well as links to translations in other languages, including American sign language. © 2022, Institute for Bulgarian Language. All rights reserved.

Challenges and Coping Measures in the Education of the Deaf and Hearing Impaired in Times of Pandemic / Desafios e Medidas de Enfrentamento na Educação dos Surdos e Deficientes Auditivos em Tempos de Pandemia

RESUMO: Com o anúncio da pandemia pela Covid-19, o isolamento social e o fechamento das escolas foram algumas das medidas adotadas para conter o contágio do coronavírus, levando a uma crise educacional mundial. Como medida reacionária, é esperado que estratégias pedagógicas tenham sido criadas para amenizar os impactos educacionais vigentes na educação dos surdos e dos deficientes auditivos. Com objetivo de traçar as principais potencialidades e fragilidades de ações e de estratégias educacionais no ensino desses indivíduos no período pandêmico em 2020 e 2021, realizou-se uma revisão bibliográfica pela busca sistematizada na plataforma da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), utilizando as palavraschave "education", "pandemic" e "deaf". As principais dificuldades no ensino remoto consistiram na falta de acesso a materiais e tecnologias para participação nas aulas, principalmente em países mais pobres, e a escassez de professores e de intérpretes em língua de sinais. Foi possível identificar que as plataformas digitais, as tecnologias assistivas (legendagem, tradução em tempo real, materiais didáticos acessíveis para surdos, entre outros), a capacitação e a alfabetização de pais, alunos e professores em língua de sinais foram protagonistas como sugestão de enfrentamento. No entanto, a participação do Estado na formação e na capacitação de professores e de tradutores intérpretes de Língua Brasileira de Sinais (Libras) são extremamente necessárias para o alcance da Educação Bilíngue inclusiva.

ABSTRACT: With the announcement of the pandemic by COVID-19, social isolation and the closing of schools were some of the measures adopted to contain the coronavirus contagion, leading to a worldwide educational crisis. As a reactionary measure, it is expected that pedagogical strategies have been created to mitigate the current educational impacts on the education of the deaf and hearing impaired. In order to outline the main strengths and weaknesses of educational actions and strategies in the teaching of these individuals in the pandemic period in 2020 and 2021, a bibliographic review was carried out through a systematic search on the platform of the Coordination for the Improvement of Higher Education Personnel (CAPES), using the keywords "education", "pandemic" and "deaf". Te main dificulties in remote teaching for the deaf consisted of the lack of access to materials and technologies for participation in classes, especially in poorer countries, and a shortage of teachers and interpreters in sign language. It was possible to identify that digital platforms, assistive technologies (subtitling, real-time translation, accessible teaching materials for the deaf, among others), training and literacy of parents, students and teachers in sign language were protagonists as a suggestion of confrontation. However, the participation of the State in the training and qualification of teachers and interpreters of Brazilian Sign Language (known by the acronym LIBRAS) are extremely necessary for the achievement of the inclusive Bilingual Education.

Online Learning Platform for Students with Disabilities: Possible Path to Progress

Due to the effects of the COVID-19 pandemic on the educational system, students cannot go to school as usual. Therefore, Ministry of Education cooperates with Distance Learning Foundation Under the Royal Patronage and Office of the National Broadcasting and Telecommunication (NBTC) to organize distance learning through the digital distance learning television. During the COVID-19 situations, schools increasingly adapt themselves to distance learning. However, schools for disabilities, Suksasongkhro Schools, and Special Education Centers cannot organize distance learning media through Distance Learning Television (DLTV) due to limitations of the students with disabilities to use the distance learning system. For example, blind students cannot access visual contents of the video media through the distance learning system so they need audio description for what they cannot see. In addition, deaf students cannot access audio contents through the distance learning, and they need sign/hand language. Thai sign language is the first language of deaf people for communicating with other people. Therefore, in this study we aim to integrate Thai sign language, closed captions, and audio description into the video soundtrack. © 2022 IEEE.

Video Conferencing with Sign language Detection

Video conferencing software has become an essential tool for communicating with one another across long distances. There are several video conferencing software that are utilised for communication all over the world. Huge numbers of people are unable to interact via spoken language and find typical video conferencing solutions difficult to use. Our project intends to solve this problem by creating a user-friendly Video Conferencing App that can identify sign language in real time and provide correct subtitles. Due to a lack of communication skills, deaf and hard of hearing persons confront several obstacles in their everyday lives. The covid epidemic has made traditional ways of communication extremely challenging for these people. Our goal is to bridge the gap by giving them a platform to showcase their skills. © 2022 IEEE.

Individuals with hearing impairment/deafness during the COVID-19 pandemic: A rapid review on communication challenges and strategies.

AIMS AND OBJECTIVES: This study aimed (a) to identify the communication issues and problems faced by individuals with hearing impairment (HI)/deafness during the COVID-19 pandemic and (b) to describe strategies to overcome the issues/problems and/or prevent their negative impact. BACKGROUND: Individuals with mild or severe HI face everyday communication problems, which have been worsened during the COVID-19 pandemic. However, no studies have summarised the available evidence to better understand the communication challenges faced by them and strategies allowing better interactions. The long duration of the outbreak-more than 2 years, with policies that have just been lifted in some countries-and the possible return of restrictions in the next Winter suggest the need to summarise evidence in the field. DESIGN AND METHODS: A rapid review is reported here in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Medline, CINAHL and Scopus databases were searched, including (a) primary or secondary studies published from January 2020 to 12 January 2022, (b) involving individuals with HI/deafness, (c) during the COVID-19 pandemic and (d) written in English. Data were extracted and summarised by using a content analysis approach. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution. RESULTS: Fourteen studies were included as follows: three non-systematic reviews, seven cross-sectional, three quasi- experimental and one qualitative study, performed mainly in the US and the UK. Face mask covering use; physical and social distancing; and information, education, rehabilitation, and healthcare accessibility have emerged as the main challenges triggering consequences such as social isolation, loneliness, poor knowledge regarding the prevention and mental health issues. Strategies mitigating these challenges are as follows: (a) adopting transparent face masks, (b) using basic skills while interacting (e.g. maintaining eye contact), (c) improving the availability of sign language interpreters, (d) allowing the presence of family members and (e) teaching basics of sign language to healthcare professionals. CONCLUSIONS AND RELEVANCE TO CLINICAL PRACTICE: Individuals with HI/deafness live with several challenges, suggesting that their vulnerability has increased tremendously during the COVID-19 pandemic. The effectiveness of strategies to overcome these difficulties should be scrutinised by conducting more research. Moreover, there should be increased awareness among all citizens by equipping them with simple strategies to communicate effectively with individuals with HI, an approach that may increase inclusiveness and prevent further negative consequences and burden.