Physically assistive robots present an opportunity to significantly increase
the well-being and independence of individuals with motor impairments or other
forms of disability who are unable to complete activities of daily living.
Speech interfaces, especially ones that utilize Large Language Models (LLMs),
can enable individuals to effectively and naturally communicate high-level
commands and nuanced preferences to robots. Frameworks for integrating LLMs as
interfaces to robots for high level task planning and code generation have been
proposed, but fail to incorporate human-centric considerations which are
essential while developing assistive interfaces. In this work, we present a
framework for incorporating LLMs as speech interfaces for physically assistive
robots, constructed iteratively with 3 stages of testing involving a feeding
robot, culminating in an evaluation with 11 older adults at an independent
living facility. We use both quantitative and qualitative data from the final
study to validate our framework and additionally provide design guidelines for
using LLMs as speech interfaces for assistive robots. Videos and supporting
files are located on our project website:
this https URL

通过结合大规模语言模型作为语音界面，我们提出了一个框架，用于将大规模语言模型应用于物理辅助机器人，以实现高水平任务规划和代码生成，并通过实证研究为物理辅助机器人的语音界面设计提供指导。

VoicePilot: 利用语言模型作为机器人辅助的语音界面

VoicePilot: Harnessing LLMs as Speech Interfaces for Physically  Assistive Robots

The ability to interact with machines using natural human language is
becoming not just commonplace, but expected. The next step is not just text
interfaces, but speech interfaces and not just with computers, but with all
machines including robots. In this paper, we chronicle the recent history of
this growing field of spoken dialogue with robots and offer the community three
proposals, the first focused on education, the second on benchmarks, and the
third on the modeling of language when it comes to spoken interaction with
robots. The three proposals should act as white papers for any researcher to
take and build upon.

自然人类语言与机器的交互能力已经不仅仅是司空见惯，而且是被期望的。下一步不仅仅是文本界面，而是语音界面；不仅仅与电脑，而是与包括机器人在内的所有机器的交互。本文记录了近期与机器人的口头对话这一快速发展领域的历史，并提出了三项建议：第一是教育，第二是基准测试，第三是在与机器人的口头交互中对语言建模。这三项建议应该成为任何研究人员借鉴和发展的白皮书。