This article discusses the prerequisites for the machine translation of sign languages. The topic is complex, including questions relating to technology, interaction design, linguistics and culture. At the moment, despite the affordances provided by the technology, automated translation between signed and spoken languages – or between sign languages – is not possible. The very need of such translation and its associated technology can also be questioned. Yet, we believe that contributing to the improvement of sign language detection, processing and even sign language translation to spoken languages in the future is a matter that should not be abandoned. However, we argue that this work should focus on all necessary aspects of sign languages and sign language user communities. Thus, a more diverse and critical perspective towards these issues is needed in order to avoid generalisations and bias that is often manifested within dominant research paradigms particularly in the fields of spoken language research and speech community.

During the past years, the development of assistive technologies for visually impaired (VI)/blind people has helped address various challenges in their lives by providing services such as obstacle detection, indoor/outdoor navigation, scene description, text reading, facial recognition and so on. This systematic mapping review is mainly focused on the scene understanding aspect (e.g., object recognition and obstacle detection) of assistive solutions. It provides guidance for researchers in this field to understand the advances during the last four and a half years. This is because deep learning techniques together with computer vision have become more powerful and accurate than ever in tasks like object detection. These advancements can bring a radical change in the development of high-quality assistive technologies for VI/blind users. Additionally, an overview of the current challenges and a comparison between different solutions is provided to indicate the pros and cons of existing approaches.