Deep Learning and Sentiment Analysis for Human-Robot Interaction
作者： Mattia Atzeni , Diego Reforgiato Recupero
DOI: 10.1007/978-3-319-98192-5_3
关键词:
摘要: In this paper we present an ongoing work showing to what extent semantic technologies, deep learning and natural language processing can be applied within the field of Human-Robot Interaction. The project has been developed for Zora, a completely programmable autonomous humanoid robot, it aims at allowing Zora interact with humans using language. robot is capable talking user understanding sentiments by leveraging our external services, such as Sentiment Analysis engine Generative Conversational Agent, which responsible generating Zora’s answers open-dialog utterances.
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