Reverse Chinese-English transliteration method and device thereof

Abstract

The invention relates to a reverse Chinese-English transliteration method and a device thereof. A Chinese transliteration name to be translated is converted into a pinyin sequence, and a statistics transliteration module is used for generating transliteration candidates; the transliteration candidates are revised into real English words by a revision module, and the revision module uses real English words collected from a great quantity of webpages to form a vocabulary; revised real English words are used to be inquiry to verify translation results, and webpage resources obtained with a search engine are used to rearrange the revised transliteration candidates; words which appear as a named entity role on the webpage are given high marks so as to filter common English words. The method can overcome the problems that a statistic model loses aphonic syllables or chooses wrong same pronouncing syllables in the process of transliteration and the like, and effectively improves precision rate of transliteration. Experiences prove that the precision rate of transliteration is improved by 17.55% in open beta.

Description

technical field [0001] The invention relates to the technical field of natural language processing, and relates to a method and a device for assisting Chinese-English reverse transliteration by means of network mining. Background technique [0002] Named entities include seven categories such as person names, place names, and institution names. Named entities convey important information in human language, and its recognition and translation are one of the key technologies in natural language processing research. In multilingual processing, the recognition and translation results of named entities directly affect the understanding of natural language. Transliteration refers to maintaining the approximation of pronunciation during translation from the source language to the target language. The vast majority of people's names are translated by transliteration, and transliteration is also an important part of place name translation and organization name translation. Therefo...

AI Technical Summary

Problems solved by technology

Second, in the statistical transliteration model, the selection of syllables is carried out according to the pronunciation, and the limiting factors between syllables are not obvious, so selection bias is prone to occur

For example, in English, the syllable "c" and the syllable "k" have similar pronunciation rules, and it is easy to make mistakes in syllable selection when reverse transliterating "Clinton / Clinton"

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