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This study investigates how individuals with visual disabilities and their sighted counterparts perceive user experiences with smart speakers. A sample of 79 participants, including 41 with visual disabilities and 38 sighted individuals, used Amazon Echo 4th Gen smart speakers. After participants used the smart speakers for one week in their daily lives, exit interviews were administered and analyzed, yielding themes of accessibility, effectiveness, enjoyment, efficiency, and privacy. Findings revealed that the voice user interfaces of smart speakers significantly enhanced accessibility and user satisfaction for those with visual disabilities, while the voice assistant Alexa contributed to fostering emotional connections. Sighted participants, while benefiting from the smart speaker's multifunctionality and efficiency, faced challenges with initial setup and advanced features. Individuals with visual disabilities raised privacy concerns. This study underscores the need for inclusive design improvements to address the diverse needs of all users. To improve user experience, future enhancements should focus on refining voice command accuracy, integrating predictive features, optimizing onboarding processes, and strengthening privacy controls. 

BACKGROUND Facial expressions are critical for conveying emotions and facilitating social interaction. Yet, little is known about how accurately sighted individuals recognize emotions facially expressed by people with visual impairments in online communication settings. OBJECTIVE This study aimed to investigate sighted individuals’ ability to understand facial expressions of six basic emotions in people with visual impairments during Zoom calls. It also aimed to examine whether education on facial expressions specific to people with visual impairments would improve emotion recognition accuracy. METHODS Sighted participants viewed video clips of individuals with visual impairments displaying facial expressions. They then identified the emotions displayed. Next, they received an educational session on facial expressions specific to people with visual impairments, addressing unique characteristics and potential misinterpretations. After education, participants viewed another set of video clips and again identified the emotions displayed. RESULTS Before education, participants frequently misidentified emotions. After education, their accuracy in recognizing emotions improved significantly. CONCLUSIONS This study provides evidence that education on facial expressions of people with visual impairments can significantly enhance sighted individuals’ ability to accurately recognize emotions in online settings. This improved accuracy has the potential to foster more inclusive and effective online interactions between people with and without visual disabilities. 

Voice-enabled technologies such as VoiceOver (screen reader) and the Seeing AI app (image recognition) have revolutionized daily tasks for people with visual disabilities, fostering greater independence and information access. However, a gap remains in understanding the user experience (UX) of these technologies. This study investigated how those with visual disabilities interacted with VoiceOver and the Seeing AI app. A convenience sample of eight participants with visual disabilities engaged in direct observations while using these technologies. The study utilized the System Usability Scale (SUS) to assess perceived usability and analyzed findings using descriptive statistics. Results indicated a poorer UX with VoiceOver compared to the Seeing AI app, with challenges identified in graphical user interfaces (GUIs), voice and gesture commands. Relevant recommendations were made to enhance usability. The study emphasizes the need for more intuitive GUIs and optimized voice/gesture interactions for users with visual disabilities. 

Many people including those with visual impairment and blindness take advantage of video conferencing tools to meet people. Video conferencing tools enable them to share facial expressions that are considered as one of the most important aspects of human communication. This study aims to advance knowledge of how those with visual impairment and blindness share their facial expressions of emotions virtually. This study invited a convenience sample of 28 adults with visual impairment and blindness to Zoom video conferencing. The participants were instructed to pose facial expressions of basic human emotions (anger, fear, disgust, happiness, surprise, neutrality, calmness, and sadness), which were video recorded. The facial expressions were analyzed using the Facial Action Coding System (FACS) that encodes the movement of specific facial muscles called Action Units (AUs). This study found that there was a particular set of AUs significantly engaged in expressing each emotion, except for sadness. Individual differences were also found in AUs influenced by the participants’ visual acuity levels and emotional characteristics such as valence and arousal levels. The research findings are anticipated to serve as the foundation of knowledge, contributing to developing emotion-sensing technologies for those with visual impairment and blindness.