This narrative review on emotional expression in Speech-to-Text (STT) interfaces with Virtual Reality (VR) aims to identify advancements, limitations, and research gaps in incorporating emotional expression into transcribed text generated by STT systems. Using a rigorous search strategy, relevant articles published between 2020 and 2024 are extracted and categorized into themes such as communication enhancement technologies, innovations in captioning, emotion recognition in AR and VR, and empathic machines. The findings reveal the evolution of tools and techniques to meet the needs of individuals with hearing impairments, showcasing innovations in live transcription, closed captioning, AR, VR, and emotion recognition technologies. Despite improvements in accessibility, the absence of emotional nuance in transcribed text remains a significant communication challenge. The study underscores the urgency for innovations in STT technology to capture emotional expressions. The research discusses integrating emotional expression into text through strategies like animated text captions, emojilization tools, and models associating emotions with animation properties. Extending these efforts into AR and VR environments opens new possibilities for immersive and emotionally resonant experiences, especially in educational contexts. The study also explores empathic applications in healthcare, education, and human-robot interactions, highlighting the potential for personalized and effective interactions. The multidisciplinary nature of the literature underscores the potential for collaborative and interdisciplinary research.

翻译：本叙事性综述聚焦于虚拟现实（VR）环境中语音转文本（STT）接口的情感表达问题，旨在梳理将情感表达融入STT系统生成转录文本的技术进展、现存局限与研究空白。通过严格的文献检索策略，本研究提取了2020年至2024年间发表的相关文献，并将其归纳为沟通增强技术、字幕生成创新、增强现实（AR）与VR中的情感识别、共情机器等主题。研究发现，为满足听障人士需求，实时转录、隐藏式字幕、AR、VR及情感识别等领域的技术工具持续演进。尽管可及性有所提升，转录文本中情感细微表达的缺失仍是人际沟通的重大挑战。本研究强调STT技术亟需创新以捕捉情感表达。论文探讨了通过动态文字字幕、表情符号化工具、情感与动画属性关联模型等策略将情感表达融入文本的方法。将这些成果拓展至AR与VR环境，为创造沉浸式情感共鸣体验开辟了新路径，尤其在教育领域具有应用前景。研究还探讨了医疗健康、教育及人机交互领域的共情应用，凸显了个性化高效交互的潜力。现有文献的多学科特性揭示了跨领域合作研究的广阔前景。