Research on the Information Processing Model of Source Language of Parallel Corpus

Abstract

The rapid development of corpus-based machine translation brings opportunities and challenges to the construction of corpus. With the continuous development of information technology, the information processing model of the source language has always been an academic hot topic in natural language processing. In the current machine translation framework, this paper proposes a parallel corpora source language processing model for translation equivalent trees. Firstly, the phrases in the source language and the target language sentence are tagged with parts of speech respectively; Secondly, the word alignment tool is used to align the phrase pairs of the source language and the target language; Syntax analysis is used to parse the source language sentence; Then, a translation equivalence tree is constructed based on the source language syntax tree, target language sentence and word alignment results. Finally, phrase translation pairs are extracted from the translation equivalent tree.