Related papers: SignBot: Learning Human-to-Humanoid Sign Language …
Humans routinely leverage semantic hints provided by signage to navigate to destinations within novel Large-Scale Indoor (LSI) environments, such as hospitals and airport terminals. However, this capability remains underexplored within the…
Previous humanoid robot research works treat the robot as a bipedal mobile manipulation platform, where only the feet and hands contact the environment. However, we humans use all body parts to interact with the world, e.g., we sit in…
Robot navigation is crucial across various domains, yet traditional methods focus on efficiency and obstacle avoidance, often overlooking human behavior in shared spaces. With the rise of service robots, socially aware navigation has gained…
Gesturing is one of the natural modes of human communication. Signs produced by gestures can have a basic meaning coupled with additional information that is layered over the basic meaning of the sign. Sign language is an important example…
Navigational signs are common aids for human wayfinding and scene understanding, but are underutilized by robots. We argue that they benefit robot navigation and scene understanding, by directly encoding privileged information on actions,…
Understanding the intentions of robots is essential for natural and seamless human-robot collaboration. Ensuring that robots have means for non-verbal communication is a basis for intuitive and implicit interaction. For this, we contribute…
Today, as seen in smart speakers, spoken dialogue technology is rapidly advancing to enable human-like interaction. However, current dialogue systems cannot pay attention not only to the content of speech, but also to the way of speaking…
Recent work have addressed the generation of human poses represented by 2D/3D coordinates of human joints for sign language. We use the state of the art in Deep Learning for motion transfer and evaluate them on How2Sign, an American Sign…
Large Language Models (LLMs) have substantially improved the conversational capabilities of social robots. Nevertheless, for an intuitive and fluent human-robot interaction, robots should be able to ground the conversation by relating…
Hand gesture serves as a critical role in sign language. Current deep-learning-based sign language recognition (SLR) methods may suffer insufficient interpretability and overfitting due to limited sign data sources. In this paper, we…
To facilitate natural and intuitive interactions with diverse user groups in real-world settings, social robots must be capable of addressing the varying requirements and expectations of these groups while adapting their behavior based on…
A long-standing goal in the field of sensory substitution is to enable sound perception for deaf and hard of hearing (DHH) people by visualizing audio content. Different from existing models that translate to hand sign language, between…
Translating human intent into robot commands is crucial for the future of service robots in an aging society. Existing Human-Robot Interaction (HRI) systems relying on gestures or verbal commands are impractical for the elderly due to…
Sign language is the preferred method of communication of deaf or mute people, but similar to any language, it is difficult to learn and represents a significant barrier for those who are hard of hearing or unable to speak. A person's…
Audio is the primary modality for human communication and has driven the success of Automatic Speech Recognition (ASR) technologies. However, such audio-centric systems inherently exclude individuals who are deaf or hard of hearing. Visual…
We humans are biased - and our robotic creations are biased, too. Bias is a natural phenomenon that drives our perceptions and behavior, including when it comes to socially expressive robots that have humanlike features. Recognizing that we…
Sign languages play a crucial role in the communication of deaf communities, but they are often marginalized, limiting access to essential services such as healthcare and education. This study proposes an automatic sign language recognition…
Isolated Sign Language Recognition (ISLR) is crucial for scalable sign language technology, yet language-specific approaches limit current models. To address this, we propose a one-shot learning approach that generalises across languages…
Deep learning models have improved sign language-to-text translation and made it easier for non-signers to understand signed messages. When the goal is spoken communication, a naive approach is to convert signed messages into text and then…
Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language…