人工智能驱动的多语言理解在社交机器人交互中的进展:广泛回顾

IF 1 4区 数学 Q1 MATHEMATICS
Yanling Dong, Xiaolan Zhou
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引用次数: 0

摘要

<abstract>< >在数字时代,人机交互正在迅速扩大,这强调了对社交机器人流利地理解和交流多种语言的需求。这不仅仅是关于解码文字,而是关于建立联系和建立信任。然而,目前许多社交机器人仅限于流行语言,服务于语言教学、医疗保健和陪伴等领域。这篇综述研究了社交机器人中人工智能驱动的语言能力,提供了它们的应用和面临的挑战的详细概述,从细微的语言理解到数据质量和文化适应性。最后,我们讨论了在机器人中集成高级语言模型的未来,以超越基本的互动,走向更深层次的情感联系。通过这一努力,我们希望为研究人员提供一个灯塔,引导他们走向一条道路,使机器人的语言熟练程度与他们真正的情感参与能力无缝融合。</p></abstract>
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancements in AI-driven multilingual comprehension for social robot interactions: An extensive review

In the digital era, human-robot interaction is rapidly expanding, emphasizing the need for social robots to fluently understand and communicate in multiple languages. It is not merely about decoding words but about establishing connections and building trust. However, many current social robots are limited to popular languages, serving in fields like language teaching, healthcare and companionship. This review examines the AI-driven language abilities in social robots, providing a detailed overview of their applications and the challenges faced, from nuanced linguistic understanding to data quality and cultural adaptability. Last, we discuss the future of integrating advanced language models in robots to move beyond basic interactions and towards deeper emotional connections. Through this endeavor, we hope to provide a beacon for researchers, steering them towards a path where linguistic adeptness in robots is seamlessly melded with their capacity for genuine emotional engagement.

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来源期刊
CiteScore
1.30
自引率
12.50%
发文量
170
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