与机器人的口语交互：研究问题与建议，来自NSF未来方向研讨会的报告
Spoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop
AI总结：
本报告基于NSF研讨会，指出当前机器人口语交互能力的局限，并从语音技术、语言建模、不确定性处理、环境适应、多模态协同、知识表示、实时处理及基础设施等八个方面提出了关键科学与工程进展建议。
摘要：
随着机器人技术的快速发展，越来越需要更有效的人机交互，以充分发挥机器人对社会的潜力。虽然口语必须是解决方案的一部分，但我们提供口语交互的能力仍然非常有限。因此，美国国家科学基金会（National Science Foundation, NSF）召开了一次研讨会，汇聚了语音、语言和机器人领域的研究人员，讨论需要采取的措施。结果就是这份报告，我们在其中指出了所需的关键科学和工程进展。\n我们的建议广泛涉及八个总体主题。第一，满足人类需求需要应对语音技术和用户体验设计中的新挑战。第二，这需要更好地对语言使用的社会和交互方面进行建模。第三，为了鲁棒性，机器人需要与用户进行更高带宽的通信并更好地处理不确定性，包括同时考虑多个假设和目标。第四，需要更强大的适应方法，使机器人能够在没有大量重新工程或收集大量训练数据的情况下，在新环境中、为新任务以及与多样化用户群体进行交流。第五，由于机器人是具身的，语音应该与注视、手势、姿态和运动等其他交流模态协同工作。第六，由于机器人在复杂环境中运行，语音组件需要能够访问关于机器人所知的物体、位置、噪声源、用户和其他人类的丰富而高效的表示。第七，由于机器人实时运行，其语音和语言处理组件也必须实时运行。第八，除了更多研究之外，我们还需要在基础设施和资源方面做更多工作，包括可共享的软件模块和内部接口、廉价的硬件、基线系统和多样化的语料库。
英文摘要：
With robotics rapidly advancing, more effective human-robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be part of the solution, our ability to provide spoken language interaction capabilities is still very limited. The National Science Foundation accordingly convened a workshop, bringing together speech, language, and robotics researchers to discuss what needs to be done. The result is this report, in which we identify key scientific and engineering advances needed. Our recommendations broadly relate to eight general themes. First, meeting human needs requires addressing new challenges in speech technology and user experience design. Second, this requires better models of the social and interactive aspects of language use. Third, for robustness, robots need higher-bandwidth communication with users and better handling of uncertainty, including simultaneous consideration of multiple hypotheses and goals. Fourth, more powerful adaptation methods are needed, to enable robots to communicate in new environments, for new tasks, and with diverse user populations, without extensive re-engineering or the collection of massive training data. Fifth, since robots are embodied, speech should function together with other communication modalities, such as gaze, gesture, posture, and motion. Sixth, since robots operate in complex environments, speech components need access to rich yet efficient representations of what the robot knows about objects, locations, noise sources, the user, and other humans. Seventh, since robots operate in real time, their speech and language processing components must also. Eighth, in addition to more research, we need more work on infrastructure and resources, including shareable software modules and internal interfaces, inexpensive hardware, baseline systems, and diverse corpora.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
