基于双语语料的单个源语词汇和目标语多词单元的对齐

多词单元包括固定搭配、多词习语和多词术语等。本文提供了一个基于双语口语语料库的自动对齐单个源语词汇和目标语多词单元的算法,算法一方面通过计算对应于同一个源语词汇,多个目标语词汇之间的互信息和t值的归一化差值的大小来衡量目标语多个词语之间的关联程度以提取多词单元,另一方面通过计算互信息和t值的平均值作为多词单元和单个源语词汇之间互为相互翻译的衡量程度,用局部最优、首尾禁用词过滤以及长词优先等策略很好地解决了这个问题。另外,对短语翻译词典的分级,有效地减少了高级别词典中非正确翻译项的数目,使得翻译词典具有更好的实用性。

Alignment of Single Source Words and Target Multi-word Units from Parallel Corpus

Multi-word unit includes steady collocation,multi-word phrase and multi-word term,this paper we provide an algorithm for automatic alignment of single source words and target multi-word units from sentence aligned parallel spoken language corpus.Mutual information has been used to extract multi-word units by many other researchers,but the retrieval results mainly depend on the identification of suitable bigrams for the initiation of the iterative process.This algorithm utilizes normalize mutual information difference and normalize t-scores difference between multi target words correspond to the same single source word to extract the multi-word units,then utilizes the even mutual information and even t-score to align the single source words and target multi-word units.In this algorithm,we have applied the Local Bests algorithm,stopword filter and long-length units preference methods et al.The grading of the lexicon can deduce the number of the incorrect entries in the high level lexicon effectively,which makes the translation lexicon more practicably.