@inproceedings{sumita-etal-1999-solutions,
title = "Solutions to problems inherent in spoken-language translation: the {ATR}-{MATRIX} approach",
author = "Sumita, Eiichiro and
Yamada, Setsuo and
Yamamoto, Kazuhide and
Paul, Michael and
Kashioka, Hideki and
Ishikawa, Kai and
Shirai, Satoshi",
booktitle = "Proceedings of Machine Translation Summit VII",
month = sep # " 13-17",
year = "1999",
address = "Singapore, Singapore",
url = "https://aclanthology.org/1999.mtsummit-1.34",
pages = "229--235",
abstract = "ATR has built a multi-language speech translation system called ATR-MATRIX. It consists of a spoken-language translation subsystem, which is the focus of this paper, together with a highly accurate speech recognition subsystem and a high-definition speech synthesis subsystem. This paper gives a road map of solutions to the problems inherent in spoken-language translation. Spoken-language translation systems need to tackle difficult problems such as ungrammaticality. contextual phenomena, speech recognition errors, and the high-speeds required for real-time use. We have made great strides towards solving these problems in recent years. Our approach mainly uses an example-based translation model called TDMT. We have added the use of extra-linguistic information, a decision tree learning mechanism, and methods dealing with recognition errors.",
}
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<abstract>ATR has built a multi-language speech translation system called ATR-MATRIX. It consists of a spoken-language translation subsystem, which is the focus of this paper, together with a highly accurate speech recognition subsystem and a high-definition speech synthesis subsystem. This paper gives a road map of solutions to the problems inherent in spoken-language translation. Spoken-language translation systems need to tackle difficult problems such as ungrammaticality. contextual phenomena, speech recognition errors, and the high-speeds required for real-time use. We have made great strides towards solving these problems in recent years. Our approach mainly uses an example-based translation model called TDMT. We have added the use of extra-linguistic information, a decision tree learning mechanism, and methods dealing with recognition errors.</abstract>
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%0 Conference Proceedings
%T Solutions to problems inherent in spoken-language translation: the ATR-MATRIX approach
%A Sumita, Eiichiro
%A Yamada, Setsuo
%A Yamamoto, Kazuhide
%A Paul, Michael
%A Kashioka, Hideki
%A Ishikawa, Kai
%A Shirai, Satoshi
%S Proceedings of Machine Translation Summit VII
%D 1999
%8 sep" 13 17"
%C Singapore, Singapore
%F sumita-etal-1999-solutions
%X ATR has built a multi-language speech translation system called ATR-MATRIX. It consists of a spoken-language translation subsystem, which is the focus of this paper, together with a highly accurate speech recognition subsystem and a high-definition speech synthesis subsystem. This paper gives a road map of solutions to the problems inherent in spoken-language translation. Spoken-language translation systems need to tackle difficult problems such as ungrammaticality. contextual phenomena, speech recognition errors, and the high-speeds required for real-time use. We have made great strides towards solving these problems in recent years. Our approach mainly uses an example-based translation model called TDMT. We have added the use of extra-linguistic information, a decision tree learning mechanism, and methods dealing with recognition errors.
%U https://aclanthology.org/1999.mtsummit-1.34
%P 229-235
Markdown (Informal)
[Solutions to problems inherent in spoken-language translation: the ATR-MATRIX approach](https://aclanthology.org/1999.mtsummit-1.34) (Sumita et al., MTSummit 1999)
ACL