Abstract
I present a translation approach based on a phrase-based maximum entropy model. To improve search performance, a beam search algorithm is exploited where the selection of the phrase candidate translation, the future probability calculation, and the pruning strategy are included. A neural network model with words and phrases is used. I obtain better translation results by the extensive experiments conducted on the real and synthetic datasets.
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Jiang, D. (2019). A Statistical Translation Approach by Network Model. In: Patnaik, S., Jain, V. (eds) Recent Developments in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 752. Springer, Singapore. https://doi.org/10.1007/978-981-10-8944-2_38
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DOI: https://doi.org/10.1007/978-981-10-8944-2_38
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