@inproceedings{su-chang-1999-customizable,
title = "A customizable, self-learning parameterized {MT} system: the next generation",
author = "Su, Keh-Yih and
Chang, Jing-Shin",
booktitle = "Proceedings of Machine Translation Summit VII",
month = sep # " 13-17",
year = "1999",
address = "Singapore, Singapore",
url = "https://aclanthology.org/1999.mtsummit-1.29",
pages = "182--190",
abstract = "In this paper, the major problems of the current machine translation systems are first outlined. A new direction, highlighting the system capability to be customizable and self-learnable, is then proposed for attacking the described problems, which are mainly resulted from the very complicated characteristics of natural languages. The proposed solution adopts an unsupervised two-way training mechanism and a parameterized architecture to acquire the required statistical knowledge, such that the system can be easily adapted to different domains and various preferences of individual users.",
}
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<abstract>In this paper, the major problems of the current machine translation systems are first outlined. A new direction, highlighting the system capability to be customizable and self-learnable, is then proposed for attacking the described problems, which are mainly resulted from the very complicated characteristics of natural languages. The proposed solution adopts an unsupervised two-way training mechanism and a parameterized architecture to acquire the required statistical knowledge, such that the system can be easily adapted to different domains and various preferences of individual users.</abstract>
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%0 Conference Proceedings
%T A customizable, self-learning parameterized MT system: the next generation
%A Su, Keh-Yih
%A Chang, Jing-Shin
%S Proceedings of Machine Translation Summit VII
%D 1999
%8 sep 13 17
%C Singapore, Singapore
%F su-chang-1999-customizable
%X In this paper, the major problems of the current machine translation systems are first outlined. A new direction, highlighting the system capability to be customizable and self-learnable, is then proposed for attacking the described problems, which are mainly resulted from the very complicated characteristics of natural languages. The proposed solution adopts an unsupervised two-way training mechanism and a parameterized architecture to acquire the required statistical knowledge, such that the system can be easily adapted to different domains and various preferences of individual users.
%U https://aclanthology.org/1999.mtsummit-1.29
%P 182-190
Markdown (Informal)
[A customizable, self-learning parameterized MT system: the next generation](https://aclanthology.org/1999.mtsummit-1.29) (Su & Chang, MTSummit 1999)
ACL