Advertisement
Published in:
2006 | OriginalPaper | Chapter
Automatic Spoken Language Translation Template Acquisition Based on Boosting Structure Extraction and Alignment
Authors : Rile Hu, Xia Wang
Published in: Chinese Spoken Language Processing
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this paper, we propose a new approach for acquiring translation templates automatically from unannotated bilingual spoken language corpora. Two basic algorithms are adopted: a grammar induction algorithm, and an alignment algorithm using Bracketing Transduction Grammar. The approach is unsupervised, statistical, data-driven, and employs no parsing procedure. The acquisition procedure consists of two steps. First, semantic groups and phrase structure groups are extracted from both the source language and the target language through a boosting procedure, in which a synonym dictionary is used to generate the seed groups of the semantic groups. Second, an alignment algorithm based on Bracketing Transduction Grammar aligns the phrase structure groups. The aligned phrase structure groups are post-processed, yielding translation templates. Preliminary experimental results show that the algorithm is effective.