Along with the development of chatbot, language models and speech technologies, there is a growing possibility and interest of creating systems able to interface with humans seamlessly through natural language or directly via speech. In this paper, we want to demonstrate that placing the research on dialog system in the broader context of embodied intelligence allows to introduce concepts taken from neurobiology and neuropsychology to define behavior architecture that reconcile hand-crafted design and artificial neural network and open the gate to future new learning approaches like imitation or learning by instruction. To do so, this paper presents a neural behavior engine that allows creation of mixed initiative dialog and action generation based on hand-crafted models using a graphical language. A demonstration of the usability of such brain-like inspired architecture together with a graphical dialog model is described through a virtual receptionist application running on a semi-public space.

翻译：随着聊天机器人、语言模型及语音技术的发展，构建能够通过自然语言或直接语音与人类无缝交互的系统正展现出日益增长的可能性与研究价值。本文旨在阐明，将对话系统研究置于具身智能的宏观框架下，能够引入来自神经生物学与神经心理学的概念，从而构建一种融合手工设计与人工神经网络的行为架构，并为未来模仿学习、指令学习等新型学习范式开辟道路。为此，本文提出一种神经行为引擎，该引擎基于图形化语言，可利用手工构建的模型实现混合主导的对话与行为生成。通过一个在半开放空间运行的虚拟接待员应用案例，展示了此类受脑启发的架构与图形化对话模型相结合的实际可用性。