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The ATR Multilingual Speech-to-Speech Translation System

Authors :
Eiichiro Sumita
Takatoshi Jitsuhiro
Hiromi Nakaiwa
Hisashi Kawai
H. Yamamoto
Konstantin Markov
Genichiro Kikui
Jinsong Zhang
Satoshi Nakamura
Seiichi Yamamoto
Source :
IEEE Transactions on Audio, Speech and Language Processing. 14:365-376
Publication Year :
2006
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2006.

Abstract

In this paper, we describe the ATR multilingual speech-to-speech translation (S2ST) system, which is mainly focused on translation between English and Asian languages (Japanese and Chinese). There are three main modules of our S2ST system: large-vocabulary continuous speech recognition, machine text-to-text (T2T) translation, and text-to-speech synthesis. All of them are multilingual and are designed using state-of-the-art technologies developed at ATR. A corpus-based statistical machine learning framework forms the basis of our system design. We use a parallel multilingual database consisting of over 600 000 sentences that cover a broad range of travel-related conversations. Recent evaluation of the overall system showed that speech-to-speech translation quality is high, being at the level of a person having a Test of English for International Communication (TOEIC) score of 750 out of the perfect score of 990.

Details

ISSN :
15587916
Volume :
14
Database :
OpenAIRE
Journal :
IEEE Transactions on Audio, Speech and Language Processing
Accession number :
edsair.doi...........d079be3b191f5b8fadef2c746222f081