Differences in biological motion perception associated with hearing status and age of signed language exposure.

This study investigates how American Sign Language (ASL) fluency and hearing status influence the perception of biological motion, using three point-light display (PLD) tasks. Prior research indicates that early exposure to ASL among deaf signers results in more rapid and effortless recognition of biological motion than hearing nonsigners, potentially due to the expertise in deciphering complex human movements or possibly due to neuroplasticity in deaf brains. However, it remains uncertain whether this advantage stems from signed language proficiency or the experience of being deaf. To explore this, we designed three PLD tasks involving viewing randomly moving dots, identifying a person from biological motion PLDs, and determining whether right-side up and inverted PLDs depict actions involving a ball. A diverse cohort of participants (N = 224) with varying ASL fluencies and hearing statuses completed the tasks online, providing us with reaction time and accuracy data. Our results demonstrate that earlier ASL exposure is associated with accuracy, especially on complex action identification tasks. Furthermore, we discovered robust evidence for a speed-accuracy trade-off in deaf participants, in which they performed more quickly but less accurately. The speed-accuracy trade-off was evident in the most difficult task, the action identification task. Further analysis of this deaf group revealed that earlier signed language acquisition led to higher accuracy in action identification task. We conclude that age of ASL exposure and hearing status both significantly contribute to variations in biological motion perception, with implications for understanding visual expertise and cognitive processing in both deaf and signing populations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Understanding the Health Care Needs of the Deaf Community Through Medical Interpreters.

For approximately 500,000 Deaf people in the United States who use American Sign Language (ASL), accessing quality health care is challenging.1 Deaf people are more likely to have been admitted to a hospital in the past 12 months and have a history of chronic illness (e.g., cardiovascular disease, arthritis, HIV, obesity) compared with those without hearing impairment.2,3 Contributing factors include lack of cultural competency, few appropriately trained ASL interpreters, insufficient clinician education, and low health literacy levels.4 Deaf is defined here as people who are culturally Deaf (values, traditions, and norms5,6) and use ASL as a primary mode of communication.

Professional Issues in the Interpreted Education of Deaf and Hard of Hearing Students.

Through in-depth interviews, this qualitative study explored the perceptions of seven teachers of students who are d/Deaf and hard of hearing (D/HH) regarding inclusive and interpreted education. The findings revealed central themes of concern including inadequate support in inclusive placements, communication modality mismatches, and insufficient quality of interpreted education. The teachers' experiences underscore the need for more comprehensive educational support systems and the development of robust support mechanisms to effectively navigate the challenges of inclusive placements for students who are D/HH. Specifically, further attention must be given to improving the qualifications, training, support, and supervision of educational interpreters facilitating education in inclusive settings. These findings have implications for multiple stakeholders, including policymakers, educators, and supportive personnel involved in shaping inclusive education practices to ensure equitable access and the creation of supportive spaces where all students can thrive.

Machine Learning-Assisted Gesture Sensor Made with Graphene/Carbon Nanotubes for Sign Language Recognition.

Gesture sensors are essential to collect human movements for human-computer interfaces, but their application is normally hampered by the difficulties in achieving high sensitivity and an ultrawide response range simultaneously. In this article, inspired by the spider silk structure in nature, a novel gesture sensor with a core-shell structure is proposed. The sensor offers a high gauge factor of up to 340 and a wide response range of 60%. Moreover, the sensor combining with a deep learning technique creates a system for precise gesture recognition. The system demonstrated an impressive 99% accuracy in single gesture recognition tests. Meanwhile, by using the sliding window technology and large language model, a high performance of 97% accuracy is achieved in continuous sentence recognition. In summary, the proposed high-performance sensor significantly improves the sensitivity and response range of the gesture recognition sensor. Meanwhile, the neural network technology is combined to further improve the way of daily communication by sign language users.

Bengali-Sign: A Machine Learning-Based Bengali Sign Language Interpretation for Deaf and Non-Verbal People.

Sign language is undoubtedly a common way of communication among deaf and non-verbal people. But it is not common among hearing people to use sign language to express feelings or share information in everyday life. Therefore, a significant communication gap exists between deaf and hearing individuals, despite both groups experiencing similar emotions and sentiments. In this paper, we developed a convolutional neural network-squeeze excitation network to predict the sign language signs and developed a smartphone application to provide access to the ML model to use it. The SE block provides attention to the channel of the image, thus improving the performance of the model. On the other hand, the smartphone application brings the ML model close to people so that everyone can benefit from it. In addition, we used the Shapley additive explanation to interpret the black box nature of the ML model and understand the models working from within. Using our ML model, we achieved an accuracy of 99.86% on the KU-BdSL dataset. The SHAP analysis shows that the model primarily relies on hand-related visual cues to predict sign language signs, aligning with human communication patterns.

Narrative reconstruction in deaf and hearing children: A comparative study in the context of Arabic diglossia.

This study explores the narrative skills of deaf and hearing children within the context of Arabic diglossia, a linguistic environment characterised by significant differences between spoken dialects and formal written language. Using Stein and Glenn's (1979) and Bruner's (1991) frameworks, the research analyses the narrative constructions of 13 hearing and 13 deaf children in Kuwait. The findings reveal that hearing children, benefiting from consistent exposure to spoken and formal Arabic, produced more coherent and detailed narratives compared to deaf children. Hearing participants also demonstrated greater vocabulary diversity. Age-related improvements in narrative skills were more pronounced among hearing children, while the impact of sign language exposure on narrative abilities was significant among deaf children. The study underscores the critical role of early language exposure and educational support in fostering narrative development, particularly in a diglossic context. These findings highlight the need for specialised educational strategies to support the unique narrative development needs of deaf children.

Cross-modal knowledge distillation for continuous sign language recognition.

Continuous Sign Language Recognition (CSLR) is a task which converts a sign language video into a gloss sequence. The existing deep learning based sign language recognition methods usually rely on large-scale training data and rich supervised information. However, current sign language datasets are limited, and they are only annotated at sentence-level rather than frame-level. Inadequate supervision of sign language data poses a serious challenge for sign language recognition, which may result in insufficient training of sign language recognition models. To address above problems, we propose a cross-modal knowledge distillation method for continuous sign language recognition, which contains two teacher models and one student model. One of the teacher models is the Sign2Text dialogue teacher model, which takes a sign language video and a dialogue sentence as input and outputs the sign language recognition result. The other teacher model is the Text2Gloss translation teacher model, which targets to translate a text sentence into a gloss sequence. Both teacher models can provide information-rich soft labels to assist the training of the student model, which is a general sign language recognition model. We conduct extensive experiments on multiple commonly used sign language datasets, i.e., PHOENIX 2014T, CSL-Daily and QSL, the results show that the proposed cross-modal knowledge distillation method can effectively improve the sign language recognition accuracy by transferring multi-modal information from teacher models to the student model. Code is available at https://github.com/glq-1992/cross-modal-knowledge-distillation_new.

An ERP investigation of perceptual vs motoric iconicity in sign production.

The type of form-meaning mapping for iconic signs can vary. For perceptually-iconic signs there is a correspondence between visual features of a referent (e.g., the beak of a bird) and the form of the sign (e.g., extended thumb and index finger at the mouth for the American Sign Language (ASL) sign BIRD). For motorically-iconic signs there is a correspondence between how an object is held/manipulated and the form of the sign (e.g., the ASL sign FLUTE depicts how a flute is played). Previous studies have found that iconic signs are retrieved faster in picture-naming tasks, but type of iconicity has not been manipulated. We conducted an ERP study in which deaf signers and a control group of English speakers named pictures that targeted perceptually-iconic, motorically-iconic, or non-iconic ASL signs. For signers (unlike the control group), naming latencies varied by iconicity type: perceptually-iconic < motorically-iconic < non-iconic signs. A reduction in the N400 amplitude was only found for the perceptually-iconic signs, compared to both non-iconic and motorically-iconic signs. No modulations of N400 amplitudes were observed for the control group. We suggest that this pattern of results arises because pictures eliciting perceptually-iconic signs can more effectively prime lexical access due to greater alignment between features of the picture and the semantic and phonological features of the sign. We speculate that naming latencies are facilitated for motorically-iconic signs due to later processes (e.g., faster phonological encoding via cascading activation from semantic features). Overall, the results indicate that type of iconicity plays role in sign production when elicited by picture-naming tasks.

Translation, Cultural Adaptation, and Content Validity of the Saudi Sign Language Version of the General Nutrition Knowledge Questionnaire.

Profoundly hearing-impaired individuals lack health-promotion education on healthy lifestyles, and this may be due to communication barriers and limited awareness of available resources. Therefore, providing understandable healthy eating knowledge and a proper education evaluation via a questionnaire is vital. The present study aimed to translate, culturally adapt, and validate the content of a Saudi sign language version of the General Nutrition Knowledge Questionnaire (GNKQ). The study followed the World Health Organization guidelines for the translation and cultural adaptation of the GNKQ, using two-phase translation (from English into Arabic and then from Arabic into Saudi sign language), including forward-translation, back-translation, and pilot testing among profoundly hearing-impaired individuals. A total of 48 videos were recorded to present the GNKQ in Saudi sign language. The scale-level content validity index (S-CVI) value was equal to 0.96, and the item-level content validity index (I-CVI) value for all questions was between 1 and 0.9, except for question 6 in section 1, which was 0.6; this discrepancy was due to religious, social, and cultural traditions. The translation, cultural adaptation, and content validity of the Saudi sign language version of the GNKQ were satisfactory. Further studies are needed to validate other measurement properties of the present translated version of this questionnaire.

Novel Wearable System to Recognize Sign Language in Real Time.

The aim of this study is to develop a practical software solution for real-time recognition of sign language words using two arms. This will facilitate communication between hearing-impaired individuals and those who can hear. We are aware of several sign language recognition systems developed using different technologies, including cameras, armbands, and gloves. However, the system we propose in this study stands out for its practicality, utilizing surface electromyography (muscle activity) and inertial measurement unit (motion dynamics) data from both arms. We address the drawbacks of other methods, such as high costs, low accuracy due to ambient light and obstacles, and complex hardware requirements, which have limited their practical application. Our software can run on different operating systems using digital signal processing and machine learning methods specific to this study. For the test, we created a dataset of 80 words based on their frequency of use in daily life and performed a thorough feature extraction process. We tested the recognition performance using various classifiers and parameters and compared the results. The random forest algorithm emerged as the most successful, achieving a remarkable 99.875% accuracy, while the naïve Bayes algorithm had the lowest success rate with 87.625% accuracy. The new system promises to significantly improve communication for people with hearing disabilities and ensures seamless integration into daily life without compromising user comfort or lifestyle quality.

An approach designed to fail deaf children and their parents and how to change it.

The matter of raising and educating deaf children has been caught up in percepts of development that are persistently inaccurate and at odds with scientific research. These percepts have negatively impacted the health and quality of life of deaf children and deaf people in general. The all too prevalent advice is to raise the child strictly orally and wait to see what happens. Only when the child is seriously behind is a completely accessible language - a sign language - introduced, and that is far too late for protecting cognitive health. The medical profession, along with others, needs to offer parents better advice and better supports so that neither the children nor their parents wait and watch as the oral-only method fails. All must take responsible action to assure an approach that succeeds.

Neural underpinnings of sentence reading in deaf, native sign language users.

The goal of this study was to investigate sentence-level reading circuits in deaf native signers, a unique group of deaf people who are immersed in a fully accessible linguistic environment from birth, and hearing readers. Task-based fMRI, functional connectivity and lateralization analyses were conducted. Both groups exhibited overlapping brain activity in the left-hemispheric perisylvian regions in response to a semantic sentence task. We found increased activity in left occipitotemporal and right frontal and temporal regions in deaf readers. Lateralization analyses did not confirm more rightward asymmetry in deaf individuals. Deaf readers exhibited weaker functional connectivity between inferior frontal and middle temporal gyri and enhanced coupling between temporal and insular cortex. In conclusion, despite the shared functional activity within the semantic reading network across both groups, our results suggest greater reliance on cognitive control processes for deaf readers, possibly resulting in greater effort required to perform the task in this group.

Combinatorial Bionic Hierarchical Flexible Strain Sensor for Sign Language Recognition with Machine Learning.

Flexible strain sensors have been widely researched in fields such as smart wearables, human health monitoring, and biomedical applications. However, achieving a wide sensing range and high sensitivity of flexible strain sensors simultaneously remains a challenge, limiting their further applications. To address these issues, a cross-scale combinatorial bionic hierarchical design featuring microscale morphology combined with a macroscale base to balance the sensing range and sensitivity is presented. Inspired by the combination of serpentine and butterfly wing structures, this study employs three-dimensional printing, prestretching, and mold transfer processes to construct a combinatorial bionic hierarchical flexible strain sensor (CBH-sensor) with serpentine-shaped inverted-V-groove/wrinkling-cracking structures. The CBH-sensor has a high wide sensing range of 150% and high sensitivity with a gauge factor of up to 2416.67. In addition, it demonstrates the application of the CBH-sensor array in sign language gesture recognition, successfully identifying nine different sign language gestures with an impressive accuracy of 100% with the assistance of machine learning. The CBH-sensor exhibits considerable promise for use in enabling unobstructed communication between individuals who use sign language and those who do not. Furthermore, it has wide-ranging possibilities for use in the field of gesture-driven interactions in human-computer interfaces.

The time course of Cantonese and Hong Kong Sign Language phonological activation: An ERP study of deaf bimodal bilingual readers of Chinese.

This study investigated Cantonese and Hong Kong Sign Language (HKSL) phonological activation patterns in Hong Kong deaf readers using the ERP technique. Two experiments employing the error disruption paradigm were conducted while recording participants' EEGs. Experiment 1 focused on orthographic and speech-based phonological processing, while Experiment 2 examined sign-phonological processing. ERP analyses focused on the P200 (180-220 ms) and N400 (300-500 ms) components. The results of Experiment 1 showed that hearing readers exhibited both orthographic and phonological effects in the P200 and N400 windows, consistent with previous studies on Chinese reading. In deaf readers, significant speech-based phonological effects were observed in the P200 window, and orthographic effects spanned both the P200 and N400 windows. Comparative analysis between the two groups revealed distinct spatial distributions for orthographic and speech-based phonological ERP effects, which may indicate the engagement of different neural networks during early processing stages. Experiment 2 found evidence of sign-phonological activation in both the P200 and N400 windows among deaf readers, which may reflect the involvement of sign-phonological representations in early lexical access and later semantic integration. Furthermore, exploratory analysis revealed that higher reading fluency in deaf readers correlated with stronger orthographic effects in the P200 window and diminished effects in the N400 window, indicating that efficient orthographic processing during early lexical access is a distinguishing feature of proficient deaf readers.

Famílias ouvintes e filhos surdos: o papel da Libras na comunicação / Hearing families and deaf children: the role of Libras in communication / Familias oyentes y niños sordos: el papel de Lengua de Señas Brasileña em la comunicación

Introdução: A Língua Brasileira de Sinais (Libras) é uma língua de natureza visuo-motora com um sistema linguístico e estrutura gramatical próprio e sua aquisição em tempo oportuno é importante para o desenvolvimento cognitivo e comunicativo da criança surda. As famílias ouvintes de crianças surdas devem se engajar no aprendizado dessa língua, uma vez que na ausência do conhecimento da Libras, podem apresentar dificuldades de comunicação e de relacionamento com seu filho surdo. Objetivo: O objetivo deste estudo foi compreender o papel da Libras na comunicação de familiares ouvintes e seus filhos surdos atendidos em um centro de reabilitação. Métodos: Trata-se de um estudo transversal, de caráter qualitativo. Foi aplicado um roteiro de entrevista semiestruturado com 10 questões abertas a pais ouvintes de crianças surdas que participam de atendimentos em um centro de reabilitação. A análise dos dados foi realizada por meio do método análise de conteúdo. Resultados: Ao todo foram entrevistadas 10 mães de crianças surdas. As idades das mães variaram de 21 a 47 anos. Nove mães afirmaram usar a Libras em casa com seus filhos todos os dias e todas relataram usá-la em atividades cotidianas da criança. Todas as mães afirmaram que o uso da Libras trouxe benefícios para o relacionamento na díade mãe-filho. Conclusão: Os achados revelam um importante papel da Libras tanto na comunicação de familiares ouvintes e seus filhos surdos, como no cotidiano desses lares. (AU)

Introduction: The Brazilian Sign Language (Libras) is a visual-motor language with its linguistic system and grammatical structure and its timely acquisition is important for deaf children's cognitive and communicative development. Deaf children's hearing families should engage in learning this language, since not knowing Libras may lead to communication and relationship difficulties with their deaf children. Objective: This study aimed to understand the role of Libras in the communication between hearing family members and their deaf children treated at a rehabilitation center. Methods: This cross-sectional qualitative study applied a semi-structured interview with 10 open-ended questions to hearing parents of deaf children who receive care at a rehabilitation center. Data were analyzed with the content analysis method. Results: Altogether, 10 mothers of deaf children were interviewed. Their ages ranged from 21 to 47 years. Nine mothers said they used Libras at home with their children every day, and all reported using it in their child's daily activities. All mothers stated that the use of Libras brought benefits to the mother-child relationship. Conclusion: The findings highlight the important role of Libras in the daily lives and communication of hearing family members and their deaf children. (AU)

Introducción: La Lengua de Señas Brasileña (Libras) es una lengua visomotora con sistema lingüístico y estructura gramatical propios y su adquisición oportuna es importante para el desarrollo cognitivo y comunicativo del niño sordo. Las familias oyentes de niños sordos deben involucrarse en el aprendizaje de este idioma, ya que en ausencia del conocimiento de Libras, pueden tener dificultades en la comunicación y las relaciones con su hijo sordo. Objetivo: El objetivo de este estudio fue comprender el papel de Libras en la comunicación de los familiares oyentes y sus hijos sordos atendidos en un centro de rehabilitación auditiva. Métodos: Se trata de un estudio transversal, cualitativo. Se aplicó un guión de entrevista semiestructurada con 10 preguntas abiertas a padres oyentes de niños sordos que participan en el cuidado en un centro de rehabilitación. El análisis de los datos se realizó mediante el método de análisis de contenido. Resultados: En total, se entrevistaron 10 madres de niños sordos. Las edades de las madres oscilaron entre 21 y 47 años. Nueve madres dijeron que usan Libras en casa con sus hijos todos los días y todas informaron que lo usan en las actividades diarias de sus hijos. Todas las madres afirmaron que el uso de Libras trajo beneficios a la relación madre-hijo. Conclusión: Los hallazgos revelan un papel importante de Libra tanto en la comunicación de los miembros oyentes de la familia y sus hijos sordos, como en la vida diaria de estos hogares. (AU)

"They still phone even though they know I'm deaf": exploring experiences of deaf people in health services in Wales, UK.

BACKGROUND: Deaf and hard of hearing people persistently experience barriers accessing health services, largely due to ineffective communication systems, a lack of flexible booking arrangements, and a lack of Deaf awareness training for health professional staff. METHODS: Face to face focus groups were conducted with 66 Deaf and hard of hearing people in Deaf clubs across Wales, UK. Thematic analysis was undertaken. RESULTS: Responses identified from focus groups are reported as barriers faced using health services, improvements that would make a difference, impact of accessibility of health services, and a potential Sign language badge for healthcare staff. CONCLUSIONS: Deaf people report that health professionals lack training on Deaf awareness and do not know how to communicate effectively with Deaf and hard of hearing people. Further research into Deaf awareness and training resources for health professionals are needed to establish what improves Deaf cultural competencies, and ultimately makes healthcare experiences more positive for people who are Deaf.

Barriers Experienced by First Nations Deaf People in the Justice System.

Anecdotal evidence strongly suggests that members of the First Nations Deaf community experience more barriers when engaging with the criminal justice system than those who are not deaf. Therefore, our purpose for writing this article is to highlight legal and policy issues related to First Nations Deaf people, including perspectives of professionals working with these communities, living in Australia who have difficulty in accessing supports within the criminal justice system. In this article, we present data from semi-structured qualitative interviews focused on four key themes: (a) indefinite detention and unfit to plead, (b) a need for an intersectional approach to justice, (c) applying the maximum extent of the law while minimizing social services-related resources, and (d) the need for language access and qualified sign language interpreters. Through this article and the related larger sustaining project, we seek to center the experiences and needs of First Nations Deaf communities to render supports for fair, just, and equitable access in the Australian criminal justice system to this historically marginalized group.

A New Method for Documenting Sign Language Productions in Schools.

PURPOSE: There are well-established guidelines for the recording, transcription, and analysis of spontaneous oral language samples by researchers, educators, and speech pathologists. In contrast, there is presently no consensus regarding methods for the written documentation of sign language samples. The Handshape Analysis Recording Tool (HART) is an innovative method for documenting and analyzing word level samples of signed languages in real time. Fluent sign language users can document the expressive sign productions of children to gather data on sign use and accuracy. METHOD: The HART was developed to document children's productions in Australian Sign Language (Auslan) in a bilingual-bicultural educational program for the Deaf in Australia. This written method was piloted with a group of fluent signing Deaf educational staff in 2014-2016, then used in 2022-2023 with a group of fluent signing professionals to examine inter- and intrarater reliability when coding parameters of sign accuracy. RESULTS: Interrater reliability measured by Gwet's Agreement Coefficient, was "good" to "very good" across the four phonological parameters that are components of every sign: location, movement, handshape, and orientation. CONCLUSIONS: The findings of this study indicate that the HART can be a reliable tool for coding the accuracy of location, orientation, movement, and handshape parameters of Auslan phonology when used by professionals fluent in Auslan. The HART can be utilized with any sign language to gather word level sign language samples in a written form and document the phonological accuracy of signed productions.