Deaf Community Research Articles

Communication Patterns of Deaf Families on TikTok: The Relationship of CODA and the Representation of Deaf Culture

This study aims to examine the communication patterns between Deaf parents and their hearing children (CODA) as represented in TikTok video content, with a particular focus on the account @jennifernatalie_. Employing Klaus Krippendorff’s qualitative content analysis approach and guided by the Revised Family Communication Patterns (RFCP) theory by Koerner & Fitzpatrick, this research identifies forms of multimodal communication, family communication patterns, and the presence of social inclusivity within parenting practices of persons with disabilities. It also explores how digital interactions function as spaces for articulating values of social inclusion. The findings reveal a dominant presence of pluralistic and consensual communication patterns, alongside the extensive use of multimodal communication. The analysis further highlights key values of inclusivity, such as emotional well-being, access to information, and equitable participation. TikTok is shown to be a representative medium for constructing positive naratives about families with disabilities.

Ethical Practices for Gaining Access for Research with Deaf Communities in South Africa: A Case of South African Sign Language.

Research ethics frameworks used in South Africa view Deafness from a biomedical perspective. Unfortunately, this could hinder research access to Deaf communities. Deaf-centric best practices draw from sociocultural perspectives instead. Motivated by this lack of Deaf-centric provisions for research with Deaf communities in the existing legal ethical frameworks in South Africa, this article examines best practices for gaining access to Deaf communities based on a broader study on South African Sign Language place names. The article synthesises ethical guidelines from literature and infuses them with the researchers' own experiences during fieldwork of the broader study to come up with best practices. These include community engagement and collaborative partnerships, seeking ethics clearance; respecting conventions of the Deaf culture, and strategically managing discontent. We conclude that these best practices could form a foundation for a future research ethics framework that considers Deaf-centric practices.

Cross-attention multi branch for Vietnamese sign language recognition: CrossViViT

Sign language serves as the primary communication medium for individuals who are deaf or hard of hearing. Despite its critical importance, barriers persist in communication between the deaf community and the broader society, primarily due to limited sign language proficiency among the general population. While automated sign language recognition (ASLR) systems leveraging machine learning technologies offer a promising solution, existing approaches face challenges in optimizing the trade-off between computational efficiency and recognition accuracy. This study presents CrossViViT, a novel architecture that integrates cross-attention mechanisms with video vision Transformer networks to address these limitations. Drawing inspiration from multi-branch network architectures that combine diverse feature perspectives for flexible image recognition, our approach achieves both computational efficiency and high accuracy. The proposed model demonstrates exceptional performance on the Vietnamese Sign Language (VSL) dataset, achieving 92.47% accuracy in recognizing 50 distinct gestures across 8510 videos while maintaining computational efficiency at approximately 629 FLOPS.

“At home, I never felt included, I always felt on the outside”: Deaf peoples’ perspectives on how inadequate access to childhood communication influences mental health outcomes

BackgroundThe prevalence of adverse mental health outcomes experienced by deaf adults – members of deaf communities connected through a shared sign language and culture is greater than that faced by their hearing counterparts. In addition to everyday life stressors, deaf people can experience further communication related stressors. For this group, early life communication and language deprivation is a significant contributing factor to subsequent adverse mental health outcomes. This study aimed to understand how deaf people viewed the impact of inadequate access to early life communication on their mental health across their life.MethodsOne-on-one semi-structured interviews were undertaken with 16 deaf Australian adults who identified as having mental health challenges. Interviews were conducted in Auslan and inductively coded using thematic analysis.ResultsParticipants attributed various forms of mental ill-health to interactions with people who could not sign, particularly within the family and school environments. Proximal stressors such as language dissonance, identity confusion, cross-cultural code-switching, and distrust were identified by participants. Distal stressors included three themes: bullying, exclusion, and marginalisation and ostracism. These stressors were perceived to be linked to experiences of mental ill health including periods of exhaustion, anger, anxiety, depression and suicidal ideation.ConclusionsThe study highlights deaf Australians’ perceived negative impacts from proximal and distal communication-related stressors during childhood on mental health outcomes. Addressing communication barriers in childhood through the implementation of interventions and support strategies may help to avoid adverse mental health outcomes for deaf adults.

From sound to story: GAS-Saudi’s graph-based solution for audio summarization in the deaf community

From sound to story: GAS-Saudi’s graph-based solution for audio summarization in the deaf community

TriFuseNet: Open-Vocabulary Sign Language Translation via Hierarchical Image-Text-Keypoint Fusion

In the field of bridging communication gaps between deaf and hearing communities, sign language recognition (SLR) and sign language translation (SLT) systems face persistent challenges in cross-lingual contexts as the understanding ability of unlabeled data is limited, the fusion depth of traditional fusion modes is insufficient, and inadequate temporal modeling, which hinder practical performance. To address these limitations, this study proposes TriFuseNet, an innovative open-vocabulary tri-modal fusion framework grounded in intersemiotic translation theory, dynamic equivalence theory, and multimodal discourse analysis, which integrates RGB images, textual semantics and skeletal keypoints through a hierarchical interaction mechanism to achieve fine-grained cross-modal alignment. The framework introduces a vision-language interaction module to bridge visual features with linguistic structures, while a bilinear state-space model (BSSM) captures long-range temporal dynamics for gesture-linguistic coherence. Additionally, region-specific attention mechanisms prioritize critical body regions to model culturally specific gestures with nuanced spatial-temporal details. Experimental evaluations on the CSL-Daily and PHOENIX-14T datasets demonstrate TriFuseNet’s superiority over state-of-the-art methods, achieving 2.3% and 1.6% reductions in word error rate (WER), respectively.

Sign Language to Speech Conversion

Human communication relies heavily on verbal and non-verbal cues, with sign language serving as a crucial method of interaction for individuals with hearing impairments. However, the communication barrier between sign language users and those unfamiliar with it remains a significant challenge. This paper presents an innovative approach to bridging this gap through an Arduino-based system that converts sign language gestures directly into speech without the use of a camera. By utilizing flex sensors and an accelerometer, this system detects hand gestures and movements, processes this data, and produces corresponding audio output. This approach offers a more accessible and portable solution compared to traditional camera-based systems, potentially revolutionizing real-time communication for the deaf community. The experimental results demonstrate a gesture recognition accuracy of 92% and a response time of under 500 milliseconds, indicating the system's viability for practical applications.

Everyday Challenges and Solutions for Individuals Aging With Deafness

Abstract Background and Objectives Approximately 11 million people in the United States self-identify as Deaf and use American Sign Language (ASL) as their primary form of communication. Yet, little is known about the challenges and solutions in everyday activities of individuals who are aging with long-term deafness. Research Design and Methods We used a community-engaged research approach to understand everyday challenges and solutions of 60 older ASL users who self-identified as Deaf. Semi-structured interviews were conducted in ASL to probe challenges and responses to those challenges across six everyday activity categories: Activities Within the Home; Activities Outside the home; Transportation; Managing Health; Shopping and Finances; and Basic Daily Activities. Results Older Deaf adults shared their lived experiences and reported challenges with unreliable technology, communication, and accessibility in the context of engaging in a myriad of everyday activities. For instance, they reported that technology alerts (e.g., airport announcements) are typically auditory, and healthcare accessibility is poor due to a lack of ASL interpreters. When probed about their solutions to these everyday challenges, participants reported relying on hearing family members, using their own methods, such as self-advocating, and using devices/technologies. Discussion and Implications Everyday challenges experienced by older Deaf adults may be mitigated by improving the reliability and accessibility of technologies used by this population, as well as improving communication accessibility across various public and private settings. Including older Deaf community members in the needs assessment and design process is critical for development of technology solutions to improve engagement in everyday activities.

Language use and identity in an ethnically heterogeneous deaf community.

Within the Hungarian Deaf minority in Romania, a combination of two distinct types of culturally rooted minority identity occurs, which generates a minority situation at several levels. Our research conducted in a multicultural city of western Romania (City A) aimed to find out what are the prevailing means of linguistic communication within the local Deaf Association community; what are the linguistic communication opportunities available for ethnic Hungarian Deaf community members; and what resources the ethnic Hungarian Deaf employ to maintain and nurture their ethno-linguistic and national identity. The research is based on a combination of quantitative and qualitative approaches: questionnaire survey, participant observation within the local association Deaf community, and life course interviews with ethnic Hungarian Deaf. We found that in case of ethnic Hungarian Deaf minority members the sense of belonging to the ethnically heterogeneous local Deaf community tends to override the belonging to the ethnically defined Hungarian Deaf sub-community. While assigning a great importance to their own ethnic identity, Hungarian minority Deaf demonstrate a high capacity and willingness to adapt to the specific sign language communicational mode of the ethnic Romanian Deaf majority in order to gain and preserve full recognition as equal members of the community.

Marcadores culturais surdos na escola: da afirmação cultural à reforma da escola

The (dis)consideration of deaf cultural markers in educational processes and practices can (dis)qualify the training paths of deaf people. In this article, we analyze the place of deaf cultural markers in school, in an exercise that establishes intersections between the perspectives and practices of educational actors regarding the presence/absence of these markers in school and their effects on deaf education. Data collection, guided by an observation guide, consisted of observing the school environment of a reference school in bilingual education for the deaf in Mozambique, for two years. During this period, we established ethnographic conversations with school managers, teachers, education assistants, deaf and hearing students. The results indicate that the school, while facing challenges, encourages the circulation of deaf cultural markers. It is concluded that the presence of these markers at school contributes to the construction of a sense of community belonging, affirmation of deaf identity and the rooting of deaf culture at school.

Making Deafness Visible: Preserving Deaf History in the Deaf Catholic Archives

This piece focuses on the work of the Deaf Catholic Archives, an archive dedicated to preserving the history of minority group whose past is underrepresented in most archival collections. Preserving deaf history in the archives is both a matter of accuracy and justice. Deaf history is a vital part of Catholic history and American history. The deaf community deserves to see its history preserved, shared, and celebrated.

A qualitative study on deaf individuals' access to health knowledge and services in Lebanon.

A qualitative study on deaf individuals' access to health knowledge and services in Lebanon.

The Responsibiligated Status: Exploring the Experiences of Hearing Children With Deaf Parents

ABSTRACTAn individual with a disability influences every member of a family. While research on families with children with disabilities is extensive, studies focusing on families with parents with disabilities remain limited. A common situation in the deaf community is a family with deaf parents and hearing children. Children of deaf adults (CODAs) experience unique family dynamics, often acting as language brokers for their deaf parents. This study explores how CODAs navigate dual roles as children and caregivers, particularly in their relationships with parents, siblings and the broader community. Using in‐depth interviews with 11 adult CODAs, this qualitative study employed reflexive thematic analysis and provided valuable insights into the distinctive dynamics of this family context. Peer debriefing among CODA and non‐CODA researchers ensured analytic trustworthiness. Findings reveal that CODAs' relationships with their parents exist on axes of responsibility and obligation. Three central themes emerged: CODAs' role as interpreters, their place within the family and their ‘responsibiligated’ status—a term coined to describe CODAs' relationships with their parents. This concept advances theoretical innovation that opens new avenues for exploring children's nuanced roles in families with distinct cultural or linguistic backgrounds, potentially informing broader discussions on family dynamics and child development.

Optimizing YOLO-Based Algorithms for Real-Time BISINDO Alphabet Detection Under Varied Lighting and Background Conditions in Computer Vision Systems

This research explores the optimization of YOLO-based computer vision algorithms for real-time recognition of Indonesian Sign Language (BISINDO) letters under diverse environmental conditions. Motivated by the communication barriers faced by the deaf and hearing communities due to limited sign language literacy, the study aims to enhance inclusivity through advanced visual detection technologies. By implementing the YOLOv5s model, the system is trained to detect and classify correct and incorrect BISINDO hand signs across 52 classes (26 correct and 26 incorrect letters), utilizing a dataset of 3,900 images augmented to 10,920 samples. Performance evaluation employs k-fold cross-validation (k=10) and confusion matrix analysis across varied lighting and background scenarios, both indoor and outdoor. The model achieves a high average precision of 0.9901 and recall of 0.9999, with robust results in indoor settings and slight degradation observed under certain outdoor conditions. These findings demonstrate the potential of YOLOv5 in facilitating real-time, accurate sign language recognition, contributing toward more accessible human-computer interaction systems for the deaf community.

Sign-Prac : Real - Time Language and Practice System

Abstract: In today’s technologically advanced world, bridging the communication gap between hearing-impaired individuals and the rest of society is a critical challenge. Sign language serves as a primary mode of communication for the deaf and hard of-hearing community. However, due to the limited number of people proficient in sign language, there exists a significant communication barrier. This project aims to address this gap by developing an intelligent, real-time sign language recognition system using deep learning techniques. The proposed system utilizes a combination of computer vision and deep learning algorithms to accurately recognize hand gestures representing sign language. Leveraging tools such as MediaPipe for hand tracking and a Convolutional Neural Network (CNN) or keypoint-based classifier for gesture classification, the system processes live video input or uploaded images to identify signs and convert them into readable text. The model is trained on a custom or publicly available sign language dataset, ensuring accuracy and robustness across various lighting conditions and hand orientations. Key modules of the system include data preprocessing, feature extraction, model training using gesture sequences, and real-time inference. The model demonstrates high classification accuracy and low latency, making it suitable for real-world applications such as education, customer service, and accessibility platforms. This project not only highlights the potential of artificial intelligence in assistive technologies but also contributes to fostering inclusivity and equal communication opportunities for all individuals, regardless of physical ability. Keywords: Sign Language Recognition (SLR), Real-Time Gesture Recognition, Deaf and Hard-of-Hearing Communication, MediaPipe, Deep Learning, Computer Vision, DualNet-SLR, Point History Network, Keypoint History Network, Streamlit Interface.

O Ensino de Matemática para Alunos Surdos: uma revisão sistemática da literatura

This article presents the results of a master’s research project of a qualitative nature, based on the methodological foundations of a Systematic Literature Review and Content Analysis. The corpus consists of articles published between 2018 and 2022 in Qualis A journals available in the CAPES Journal Portal. The research aimed to answer the following question: “What does the literature reveal about the teaching of Mathematics to deaf students, and how can it be made more inclusive?” The data analysis led to the development of six thematic categories that revealed gaps in teacher training and inclusive pedagogical practices that value Brazilian Sign Language (Libras), the importance of visual resources, and the specificities of Deaf Culture. The study also pointed out the scarcity of mathematical vocabulary in Libras and the urgent need to disseminate bilingual education and SignWriting. This study aims to contribute to the field of Mathematics Education by offering theoretical and practical insights that can guide teachers and institutions in promoting more accessible and equitable teaching for deaf students.

Hard of hearing learners in a school for the deaf: A case study in the Eastern Cape province

BackgroundLearners who are hard of hearing (HoH) in the Eastern Cape typically attend special schools for the deaf. Failures in mainstream schools result in learners being placed at a special school where South African Sign Language (SASL) is used as the medium of instruction. This is despite learners having residual hearing compared to their d/Deaf peers. This scenario is common in South Africa and often poses a dilemma for professionals in the field.ObjectivesThe objectives of this study were to describe the contextual factors of the audiological history (cause of hearing loss, age of diagnosis and use of amplification) and the communicative function of learners, to explore the school experiences of HoH learners in terms of their classroom and social experiences and to describe learners’ views on self-identity.MethodThe study participants consisted of two groups, learners (eight) and their parents or caregivers (six). A case study design was used. The data sources for the study included participant interviews, direct observations and a review of records. Thematic analysis and descriptive statistics were used for data analysis.ResultsThe learners used SASL and had positive school experiences. They could communicate effectively in SASL and identified with the school community and Deaf Culture. Learners used speech-reading and some oral language. Parents and caregivers could not communicate in SASL with their children.ConclusionLearners who are HoH had a sense of belonging in a school for the deaf where SASL is used as a medium of instruction.ContributionThe findings contribute to the understanding of learners who are HoH in the South African Special Needs Education context where research of this nature is lacking.

Understanding the context of mental health in deaf populations is important.

This commentary highlights the importance of understanding mental health in deaf populations within the context of language development and access. The authors, who are all Deaf professionals, emphasize that language deprivation-not hearing loss directly-is a primary cause of many mental health issues in deaf communities, and advocate for the inclusion of deaf experts in research and publications concerning deaf individuals' mental health.

Al Powered Real-Time Sign Language Detection and Translation System for Inclusive Communication Between Deaf and Hearing Communities Worldwide

Abstract - Sign language is a vital communication tool for individuals who are deaf or hard of hearing, yet it remains largely inaccessible to the wider population. This project aims to address this barrier by developing a sign language recognition system that converts hand gestures into text, followed by text-to-speech (TTS) conversion. The system utilizes Convolutional Neural Networks (CNNs) to recognize static hand gestures and translate them into corresponding textual representations. The text is then processed by a TTS engine, which generates spoken language, making it comprehensible to individuals who are not familiar with sign language. The approach leverages deep learning techniques to improve gesture recognition accuracy, particularly in diverse real-world scenarios. By training the CNN on a comprehensive dataset of sign language gestures, the model is able to learn important features such as hand shape, orientation, and motion, which are critical for identifying specific signs. Keywords: Sign Language Recognition-Gesture to Text-Text to Speech (TTS)-Convolutional Neural Networks (CNN)-Deep Learning-Hand Gesture Recognition-Assistive Technology-Real-Time Translation-Speech Synthesis-Accessibility-Inclusivity-Communication Aid-Deaf and Hard of Hearing-Human-Computer Interaction-Static Hand Gestures

Preliminary development of the deaf childhood experiences scale.

We describe here the initial creation and validation of a tool designed to quantify certain unique life experiences of deaf individuals. The Deaf Childhood Experiences Scale (DCES) aims to provide empirical data on uniquely deaf life factors with the long-term goal of better understanding education, health, and quality of life outcomes among deaf populations. The methodology involved a mixed-methods approach of qualitative interviews with deaf community members to inform the creation of a quantitative assessment. This first version of the DCES comprises two main constructs-Language and Access, and Belonging-and was validated against Adverse Childhood Experiences questions, revealing a weak but significant correlation (r(568) = .18, p = < .001). The DCES offers a novel approach to better measure, and eventually understand the impact of, childhood experiences of deaf people that are likely salient for quality of life outcomes. Future work includes more validation efforts, plans for American sign language translation, parent and teacher versions, and further item revisions.