论文标题
使用本体论和转移学习与XAI的语言学习聊天机器人的设计和实施
The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning
论文作者
论文摘要
在本文中，我们提出了一个基于转移学习的英语学习聊天机器人，该聊天机器人由GPT-2产生的输出可以通过通过微调数据集扎根的相应本体图表来解释。我们设计了三个用于系统的英语学习的级别，包括语音识别和发音校正的语音级别，特定域对话的语义级别以及英语中自由式对话的模拟 - 语言聊天机器人交流的最高水平作为自由风格的对话代理。为了进行学术贡献，我们遵循XAI（可解释的人工智能）的概念来解释自由式对话的性能，以可视化Bionics中神经网络的连接，并解释语言模型的输出句子。从实施角度来看，我们的语言学习代理将微信中的微型编程整合为前端，并微调的转移学习模型作为后端，以解释本体论图的响应。
In this paper, we proposed a transfer learning-based English language learning chatbot, whose output generated by GPT-2 can be explained by corresponding ontology graph rooted by fine-tuning dataset. We design three levels for systematically English learning, including phonetics level for speech recognition and pronunciation correction, semantic level for specific domain conversation, and the simulation of free-style conversation in English - the highest level of language chatbot communication as free-style conversation agent. For academic contribution, we implement the ontology graph to explain the performance of free-style conversation, following the concept of XAI (Explainable Artificial Intelligence) to visualize the connections of neural network in bionics, and explain the output sentence from language model. From implementation perspective, our Language Learning agent integrated the mini-program in WeChat as front-end, and fine-tuned GPT-2 model of transfer learning as back-end to interpret the responses by ontology graph.
