Abstract
Due to the rapid development of smart city, Hybrid Information Centric-Networking (HICN) emerges as a promising technology to enable the power of smart city. One of the most important application is the smart English translation, which becomes more and more popular with the process of Internationalization. In this work, we focus on studying the intelligent English translation is smart city using the HICN technology. Particularly, a method using collaborative machine learning and quality estimation technique is proposed, which sets a fixed threshold to filter pseudo-parallel data during unsupervised neural machine translation training. The quality estimation is used to evaluate and screen the pseudo-parallel data with high performance generated during reverse translation training. The results indicate that the proposed method outperforms the state-of-the-art methods.
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