Automatic Spoken-to-Sign Language Translation: A Review of Key Technologies, Limitations, and Interdisciplinary Opportunities - Ferreira, William; Tanajura, Pedro; Simas, João Pedro; Ferreira, Yasmim Thasla Santos; Soussa, Márcio; Winkler, Ingrid (Anais do Simpósio de Realidade Virtual e Aumentada (SVR), 2025)
The communication barrier between deaf and hearing individuals remains a global challenge in academic, professional, and social contexts. Although numerous countries officially recognize their respective national sign languages, the availability of automatic, real-time, and linguistically accurate translation systems from spoken into sign languages remains limited in both coverage and quality. This paper reviews the key technologies, limitations, and interdisciplinary opportunities on computational approaches for real-time spoken-to-sign language translation. Following a systematic search of IEEE Xplore, Scopus, ACM Digital Library, and SciELO databases conducted in accordance with PRISMA guidelines, covering research published between 2020 and 2024, and applying predefined inclusion and exclusion criteria, fifteen peer-reviewed studies were identified. The analysis of key enabling technologies, including automatic speech recognition (ASR), natural language processing (NLP), 3D avatar animation, and emerging applications in virtual reality (VR), identified major linguistic and technical challenges, such as the representation of non-manual signals, multimodal grammar processing, and the scarcity of high-quality datasets. Results revealed four dominant technological approaches: ASR–NLP pipelines, avatar-based rendering systems, VR/AR learning tools, and sensor-based gesture recognition platforms. Despite substantial advances, major limitations include low representation of non-manual signals, restricted vocabulary coverage, and high hardware dependency. The review concludes that interdisciplinary research integrating linguistics, AI, and human-computer interaction is essential for developing culturally adaptive and accessible solutions for the deaf community.