Humboldt Research Group 'Evolution of Communication', Max Planck Institute for Ornithology, 82319 Seewiesen, Germany; Anthropological Institute and Museum, University of Zurich, 8057 Zurich, Switzerland.
Neurosci Biobehav Rev. 2017 Sep;80:201-209. doi: 10.1016/j.neubiorev.2017.05.005. Epub 2017 May 10.
In the quest to bridge the gulf between the fields of linguistics and animal communication, interest has recently been drawn to turn-taking behavior in social interaction. Vocal turn-taking is the core form of language usage in humans, and has been examined in numerous species of birds and primates. Recent studies on great apes have shown that they engage in a bodily form, gestural turn-taking, to achieve mutual communicative goals. However, most studies on turn-taking neglected the fact that signals are prevalently perceived and produced in a multimodal format. Here, I propose that research on animal communication may benefit a more holistic and dynamic approach: studying turn-taking using a multimodal, conservation-analytic framework. I will discuss recent comparative research that implemented this approach via a specific set of parameters. In sum, I argue that a conversation-analytic framework might help substantially to pinpoint the ways in which crucial components of language are embodied in the 'human interaction engine'.
在语言学和动物交流领域之间架起桥梁的探索中，人们最近对社会互动中的交替行为产生了兴趣。在人类中，轮流说话是语言使用的核心形式，并且已经在许多鸟类和灵长类动物中进行了研究。最近对大型类人猿的研究表明，它们采用身体形式，即手势轮流，来实现共同的交际目标。然而，大多数关于轮流的研究都忽略了这样一个事实，即信号主要是以多模态的形式被感知和产生的。在这里，我提出动物交流的研究可能会受益于更全面和动态的方法：使用多模态、守恒分析框架来研究轮流。我将讨论最近通过一组特定参数实施这种方法的比较研究。总之，我认为会话分析框架可以帮助我们准确地指出语言的关键组成部分是如何体现在“人类互动引擎”中的。
