A Hybrid Word Alignment Approach to Improve Translation Lexicons with Compound Words and Idiomatic Expressions
Nasredine Semmar, Christophe Servan, Gaël de Chalendar, Benoît Le Ny, Jean-Jacques Bouzaglou · 2010
In this paper, we present a hybrid approach to align single words, compound words and idiomatic expressions from bilingual parallel corpora. The objective is to develop, improve and maintain automatically translation lexicons. This approach combines linguistic and statistical information in order to improve word alignment results. The linguistic improvements taken into account refer to the use of an existing bilingual lexicon, named entities recognition, grammatical tags matching and detection of syntactic dependency relations between words. Statistical information refer to the number of occurrences of repeated words, their positions in the parallel corpus and their lengths in terms of number of characters. Single-word alignment uses an existing bilingual lexicon, named entities and cognates detection and grammatical tags matching. Compound-word alignment consists in establishing correspondences between the compound words of the source sentence and the compound words of the target sentences. A syntactic analysis is applied on the source and target sentences in order to extract dependency relations between words and to recognize compound words. Idiomatic expressions alignment starts with a monolingual term extraction