摘要翻译：
人工智能领域几十年的工作集中在开发新一代系统上，这些系统可以通过与世界的交互来获取知识。然而，直到最近，大多数这样的尝试都是以研究为基础的，这些研究主要将语言现象视为与大脑和身体分离的现象。这可能会使人相信，为了模拟语言行为，只要开发出在任何计算机器上都能工作的抽象表示上操作的“软件”就足够了。这张图片是不准确的几个原因，这些原因在本文中被阐明，并延伸到感觉运动和语义共振之外。从回顾研究开始，我列举了几个反对非具体化语言的异质论点，试图得出结论，以发展具体化的多感官代理，这些代理与他们的环境进行口头和非口头交流。如果不考虑人脑的结构和体现，准确地复制语言习得、理解、产出或非语言行为的过程是不现实的。虽然机器人与人类远不是同构的，但它们可以在优化过程、对环境刺激的反应性和敏感性以及在情景人机交互中受益于加强关联连接。多感官整合的概念应该扩展到包括语言输入和从时间上重合的感官印象中结合起来的互补信息。
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英文标题：
《Developing Embodied Multisensory Dialogue Agents》
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作者：
Micha{\l} B. Paradowski
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最新提交年份：
2012
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Computation and Language        计算与语言
分类描述：Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.
涵盖自然语言处理。大致包括ACM科目I.2.7类的材料。请注意，人工语言（编程语言、逻辑学、形式系统）的工作，如果没有明确地解决广义的自然语言问题（自然语言处理、计算语言学、语音、文本检索等），就不适合这个领域。
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英文摘要：
  A few decades of work in the AI field have focused efforts on developing a new generation of systems which can acquire knowledge via interaction with the world. Yet, until very recently, most such attempts were underpinned by research which predominantly regarded linguistic phenomena as separated from the brain and body. This could lead one into believing that to emulate linguistic behaviour, it suffices to develop 'software' operating on abstract representations that will work on any computational machine. This picture is inaccurate for several reasons, which are elucidated in this paper and extend beyond sensorimotor and semantic resonance. Beginning with a review of research, I list several heterogeneous arguments against disembodied language, in an attempt to draw conclusions for developing embodied multisensory agents which communicate verbally and non-verbally with their environment. Without taking into account both the architecture of the human brain, and embodiment, it is unrealistic to replicate accurately the processes which take place during language acquisition, comprehension, production, or during non-linguistic actions. While robots are far from isomorphic with humans, they could benefit from strengthened associative connections in the optimization of their processes and their reactivity and sensitivity to environmental stimuli, and in situated human-machine interaction. The concept of multisensory integration should be extended to cover linguistic input and the complementary information combined from temporally coincident sensory impressions.
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PDF链接：
https://arxiv.org/pdf/1111.7190