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题目: 在微软小冰做好玩儿的研究
报告人: 宋睿华 微软小冰首席科学家 微软(亚洲)互联网工程院
摘要: 与众多厂商投入问答或任务型对话不同,微软小冰选择深耕细作闲聊领域。有人认为,闲聊没有显而易见的用处,而我却被这种好玩儿的对话深深吸引。在这次讲座中,我想跟大家介绍小冰在最近一年里从模仿到创造再到多模态理解的一些成果,希望给大家展示一些机器学习能做的好玩儿的应用。今天,小冰已不仅是一个聊天机器人,它所代表的情感计算框架涵盖了长程对话、人工智能创造和多模态等多方面的研究课题,支撑着未来塑造不同类型和性格的AI beings(硅基人类)。
Embodied conversational agents (ECAs) benefit from non-verbal behavior for natural and efficient interaction with users. Gesticulation - hand and arm movements accompanying speech - is an essential part of non-verbal behavior. Gesture generation models have been developed for several decades: starting with rule-based and ending with mainly data-driven methods. To date, recent end-to-end gesture generation methods have not been evaluated in a real-time interaction with users. We present a proof-of-concept framework, which is intended to facilitate evaluation of modern gesture generation models in interaction. We demonstrate an extensible open-source framework that contains three components: 1) a 3D interactive agent; 2) a chatbot backend; 3) a gesticulating system. Each component can be replaced, making the proposed framework applicable for investigating the effect of different gesturing models in real-time interactions with different communication modalities, chatbot backends, or different agent appearances. The code and video are available at the project page https://nagyrajmund.github.io/project/gesturebot.