Tell Me Where To Go: Voice-Controlled Hands-Free Locomotion for Virtual Reality Systems.

VR(2023)

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摘要
As locomotion is an important factor in improving Virtual Reality (VR) immersion and usability, research in this area has been and continues to be a crucial aspect for the success of VR applications. In recent years, a variety of techniques have been developed and evaluated, ranging from abstract control, vehicle, and teleportation techniques to more realistic techniques such as motion, gestures, and gaze. However, when it comes to hands-free scenarios, for example to increase the overall accessibility of an application or in medical scenarios under sterile conditions, most of the announced techniques cannot be applied. This is where the use of speech as an intuitive means of navigation comes in handy. As systems become more capable of understanding and producing speech, voice interfaces become a valuable alternative for input on all types of devices. This takes the quality of hands-free interaction to a new level. However, intuitive user-assisted speech interaction is difficult to realize due to semantic ambiguities in natural language utterances as well as the high real-time requirements of these systems. In this paper, we investigate steering-based locomotion and selection-based locomotion using three speech-based, hands-free methods and compare them with leaning as an established alternative. Our results show that landmark-based locomotion is a convenient, fast, and intuitive way to move between locations in a VR scene. Furthermore, we show that in scenarios where landmarks are not available, number grid-based navigation is a successful solution. Based on this, we conclude that speech is a suitable alternative in hands-free scenarios, and exciting ideas are emerging for future work focused on developing hands-free ad hoc navigation systems for scenes where landmarks do not exist or are difficult to articulate or recognize.
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关键词
Human-centered computing, Human computer interaction (HCI)-,-Computing methodologies-, Artificial intelligence, Natural language processing Speech recognition
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