DocumentCode
835642
Title
The ATR multilingual speech-to-speech translation system
Author
Nakamura, Satoshi ; Markov, Konstantin ; Nakaiwa, Hiromi ; Kikui, Genichiro ; Kawai, Hisashi ; Jitsuhiro, Takatoshi ; Zhang, Jin-Song ; Yamamoto, Hirofumi ; Sumita, Eiichiro ; Yamamoto, Seiichi
Volume
14
Issue
2
fYear
2006
fDate
3/1/2006 12:00:00 AM
Firstpage
365
Lastpage
376
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.
Keywords
language translation; learning (artificial intelligence); speech recognition; statistical analysis; word processing; ATR multilingual speech-to-speech translation system; corpus-based statistical machine learning framework; large-vocabulary continuous speech recognition; machine text-to-text translation; parallel multilingual database; text-to-speech synthesis; Databases; History; Humans; Machine learning; Natural languages; Speech recognition; Speech synthesis; Surface-mount technology; System testing; Vocabulary; Example-based machine translation (EBMT); minimum description length (MDL); multiclass language model; speech-to-speech translation (S2S); statistical machine translation (SMT); successive state splitting (SSS); text-to-speech (TTS) conversion;
fLanguage
English
Journal_Title
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher
ieee
ISSN
1558-7916
Type
jour
DOI
10.1109/TSA.2005.860774
Filename
1597243
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