Title
Construction of Chunk-Aligned Bilingual Lecture Corpus for Simultaneous Machine Translation
Abstract
With the development of speech and language processing, speech translation systems have been developed. These studies target spoken dialogues, and employ consecutive interpretation, which uses a sentence as the translation unit. On the other hand, there exist a few researches about simultaneous interpreting, and recently, the language resources for promoting simultaneous interpreting research, such as the publication of an analytical large-scale corpus, has been prepared. For the future, it is necessary to make the corpora more practical toward realization of a simultaneous interpreting system. In this paper, we describe the construction of a bilingual corpus which can be used for simultaneous lecture interpreting research. Simultaneous lecture interpreting systems are required to recognize translation units in the middle of a sentence, and generate its translation at the proper timing. We constructed the bilingual lecture corpus by the following steps. First, we segmented sentences in the lecture data into semantically meaningful units for the simultaneous interpreting. And then, we assigned the translations to these units from the viewpoint of the simultaneous interpreting. In addition, we investigated the possibility of automatically detecting the simultaneous interpreting timing from our corpus.
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
machine translation
Field
DocType
Citations 
Rule-based machine translation,Example-based machine translation,Computer science,Machine translation,Text corpus,Speech recognition,Machine translation software usability,Artificial intelligence,Corpus linguistics,Natural language processing,Computer-assisted translation,Speech translation
Conference
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Masaki Murata100.34
Tomohiro Ohno23110.06
Shigeki Matsubara317943.41
Yasuyoshi Inagaki424344.27