Improved Arabic–Chinese Machine Translation with Linguistic Input Features

Improved Arabic–Chinese Machine Translation with Linguistic Input Features

This study presents linguistically augmented models of phrase-based statistical machine translation (PBSMT) using different linguistic features (factors) on the top of the source surface form. The architecture addresses two major problems occurring in machine translation, namely the poor performance...

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Bibliographic Details
Main Authors: Fares Aqlan, Xiaoping Fan, Abdullah Alqwbani, Akram Al-Mansoub
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Future Internet
Subjects:
Arabic morphology
factored translation model
phrase-based machine translation
pre-processing
statistical machine translation
Online Access:http://www.mdpi.com/1999-5903/11/1/22

Internet

http://www.mdpi.com/1999-5903/11/1/22

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