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The ATR Multilingual Speech-to-Speech Translation System
- 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.
- Subjects :
- Acoustics and Ultrasonics
business.industry
Computer science
Speech recognition
Speech synthesis
computer.software_genre
Speech processing
Machine translation software usability
TOEIC
Example-based machine translation
Rule-based machine translation
Computer-assisted translation
Evaluation of machine translation
Artificial intelligence
Electrical and Electronic Engineering
business
computer
Natural language processing
Subjects
Details
- ISSN :
- 15587916
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Audio, Speech and Language Processing
- Accession number :
- edsair.doi...........d079be3b191f5b8fadef2c746222f081