Abstract
In this paper, we describe some concepts of language models beyond the usually used standard trigram and use such language models for statistical machine translation. In statistical machine translation the language model is the a-priori knowledge source of the system about the target language. One important requirement for the language model is the correct word order, given a certain choice of words, and to score the translations generated by the translation model Pr(f1J/eI1), in view of the syntactic context. In addition to standard m-grams with long histories, we examine the use of Part-of-Speech based models as well as linguistically motivated grammars with stochastic parsing as a special type of language model. Translation results are given on the VERBMOBIL task, where translation is performed from German to English, with vocabulary sizes of 6500 and 4000 words, respectively.- Anthology ID:
- 2000.iwpt-1.23
- Volume:
- Proceedings of the Sixth International Workshop on Parsing Technologies
- Month:
- February 23-25
- Year:
- 2000
- Address:
- Trento, Italy
- Editors:
- Alberto Lavelli, John Carroll, Robert C. Berwick, Harry C. Bunt, Bob Carpenter, John Carroll, Ken Church, Mark Johnson, Aravind Joshi, Ronald Kaplan, Martin Kay, Bernard Lang, Alon Lavie, Anton Nijholt, Christer Samuelsson, Mark Steedman, Oliviero Stock, Hozumi Tanaka, Masaru Tomita, Hans Uszkoreit, K. Vijay-Shanker, David Weir, Mats Wiren
- Venue:
- IWPT
- SIG:
- SIGPARSE
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 231–241
- Language:
- URL:
- https://aclanthology.org/2000.iwpt-1.23
- DOI:
- Bibkey:
- Cite (ACL):
- Hassan Sawaf, Kai Schütz, and Hermann Ney. 2000. On the Use of Grammar Based Language Models for Statistical Machine Translation. In Proceedings of the Sixth International Workshop on Parsing Technologies, pages 231–241, Trento, Italy. Association for Computational Linguistics.
- Cite (Informal):
- On the Use of Grammar Based Language Models for Statistical Machine Translation (Sawaf et al., IWPT 2000)
- Copy Citation:
- PDF:
- https://aclanthology.org/2000.iwpt-1.23.pdf
Export citation
@inproceedings{sawaf-etal-2000-use,
title = "On the Use of Grammar Based Language Models for Statistical Machine Translation",
author = {Sawaf, Hassan and
Sch{\"u}tz, Kai and
Ney, Hermann},
editor = "Lavelli, Alberto and
Carroll, John and
Berwick, Robert C. and
Bunt, Harry C. and
Carpenter, Bob and
Carroll, John and
Church, Ken and
Johnson, Mark and
Joshi, Aravind and
Kaplan, Ronald and
Kay, Martin and
Lang, Bernard and
Lavie, Alon and
Nijholt, Anton and
Samuelsson, Christer and
Steedman, Mark and
Stock, Oliviero and
Tanaka, Hozumi and
Tomita, Masaru and
Uszkoreit, Hans and
Vijay-Shanker, K. and
Weir, David and
Wiren, Mats",
booktitle = "Proceedings of the Sixth International Workshop on Parsing Technologies",
month = feb # " 23-25",
year = "2000",
address = "Trento, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2000.iwpt-1.23",
pages = "231--241",
abstract = "In this paper, we describe some concepts of language models beyond the usually used standard trigram and use such language models for statistical machine translation. In statistical machine translation the language model is the a-priori knowledge source of the system about the target language. One important requirement for the language model is the correct word order, given a certain choice of words, and to score the translations generated by the translation model $\textrm{Pr}(f_1^J/e^I_1)$, in view of the syntactic context. In addition to standard $m$-grams with long histories, we examine the use of Part-of-Speech based models as well as linguistically motivated grammars with stochastic parsing as a special type of language model. Translation results are given on the VERBMOBIL task, where translation is performed from German to English, with vocabulary sizes of 6500 and 4000 words, respectively.",
}
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%0 Conference Proceedings %T On the Use of Grammar Based Language Models for Statistical Machine Translation %A Sawaf, Hassan %A Schütz, Kai %A Ney, Hermann %Y Lavelli, Alberto %Y Carroll, John %Y Berwick, Robert C. %Y Bunt, Harry C. %Y Carpenter, Bob %Y Church, Ken %Y Johnson, Mark %Y Joshi, Aravind %Y Kaplan, Ronald %Y Kay, Martin %Y Lang, Bernard %Y Lavie, Alon %Y Nijholt, Anton %Y Samuelsson, Christer %Y Steedman, Mark %Y Stock, Oliviero %Y Tanaka, Hozumi %Y Tomita, Masaru %Y Uszkoreit, Hans %Y Vijay-Shanker, K. %Y Weir, David %Y Wiren, Mats %S Proceedings of the Sixth International Workshop on Parsing Technologies %D 2000 %8 feb 23 25 %I Association for Computational Linguistics %C Trento, Italy %F sawaf-etal-2000-use %X In this paper, we describe some concepts of language models beyond the usually used standard trigram and use such language models for statistical machine translation. In statistical machine translation the language model is the a-priori knowledge source of the system about the target language. One important requirement for the language model is the correct word order, given a certain choice of words, and to score the translations generated by the translation model Pr(f₁^J/e^I₁), in view of the syntactic context. In addition to standard m-grams with long histories, we examine the use of Part-of-Speech based models as well as linguistically motivated grammars with stochastic parsing as a special type of language model. Translation results are given on the VERBMOBIL task, where translation is performed from German to English, with vocabulary sizes of 6500 and 4000 words, respectively. %U https://aclanthology.org/2000.iwpt-1.23 %P 231-241
Markdown (Informal)
[On the Use of Grammar Based Language Models for Statistical Machine Translation](https://aclanthology.org/2000.iwpt-1.23) (Sawaf et al., IWPT 2000)
- On the Use of Grammar Based Language Models for Statistical Machine Translation (Sawaf et al., IWPT 2000)
ACL
- Hassan Sawaf, Kai Schütz, and Hermann Ney. 2000. On the Use of Grammar Based Language Models for Statistical Machine Translation. In Proceedings of the Sixth International Workshop on Parsing Technologies, pages 231–241, Trento, Italy. Association for Computational Linguistics.