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A Neural Network based Vietnamese Chatbot

机译:基于神经网络的越南聊天

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摘要

Nowadays, chatbot is a hot topic, chatbots are built from generative models are gaining success. The purpose of this article is to build a Vietnamese chatbot based on the seq2seq model incorporating the attention mechanism. We have built the model and tested on deep learning framework Pytorch using GPU. The model was trained end-to-end with no hand-crafted rules. Model is built from a small dataset and can generate responses to a user. However, generated responses still need to be improved to get a meaningful conversation.
机译:如今,Chatbot是一个热门话题,Chatbots由生成模型构建是获得成功的。本文的目的是基于包含注意机制的SEQ2SEQ模型来构建越南聊天。我们已经建立了模型,并使用GPU对深度学习框架Pytorch进行了测试。该模型的培训结束于终端,没有手工制作的规则。模型由小型数据集构建,可以为用户生成响应。但是,生成的响应仍然需要改进以获得有意义的对话。

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