@inproceedings{hoang-etal-2016-fast,
title = "Fast, Scalable Phrase-Based {SMT} Decoding",
author = "Hoang, Hieu and
Bogoychev, Nikolay and
Schwartz, Lane and
Junczys-Dowmunt, Marcin",
editor = "Green, Spence and
Schwartz, Lane",
booktitle = "Conferences of the Association for Machine Translation in the Americas: MT Researchers' Track",
month = oct # " 28 - " # nov # " 1",
year = "2016",
address = "Austin, TX, USA",
publisher = "The Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2016.amta-researchers.4",
pages = "40--52",
abstract = "The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial use has increased, there is need for software that is optimized for commercial requirements, in particular, fast phrase-based decoding and more efficient utilization of modern multicore servers. In this paper we re-examine the major components of phrase-based decoding and decoder implementation with particular emphasis on speed and scalability on multicore machines. The result is a drop-in replacement for the Moses decoder which is up to fifteen times faster and scales monotonically with the number of cores.",
}
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%0 Conference Proceedings
%T Fast, Scalable Phrase-Based SMT Decoding
%A Hoang, Hieu
%A Bogoychev, Nikolay
%A Schwartz, Lane
%A Junczys-Dowmunt, Marcin
%Y Green, Spence
%Y Schwartz, Lane
%S Conferences of the Association for Machine Translation in the Americas: MT Researchers’ Track
%D 2016
%8 oct 28 nov 1
%I The Association for Machine Translation in the Americas
%C Austin, TX, USA
%F hoang-etal-2016-fast
%X The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial use has increased, there is need for software that is optimized for commercial requirements, in particular, fast phrase-based decoding and more efficient utilization of modern multicore servers. In this paper we re-examine the major components of phrase-based decoding and decoder implementation with particular emphasis on speed and scalability on multicore machines. The result is a drop-in replacement for the Moses decoder which is up to fifteen times faster and scales monotonically with the number of cores.
%U https://aclanthology.org/2016.amta-researchers.4
%P 40-52
Markdown (Informal)
[Fast, Scalable Phrase-Based SMT Decoding](https://aclanthology.org/2016.amta-researchers.4) (Hoang et al., AMTA 2016)
ACL
- Hieu Hoang, Nikolay Bogoychev, Lane Schwartz, and Marcin Junczys-Dowmunt. 2016. Fast, Scalable Phrase-Based SMT Decoding. In Conferences of the Association for Machine Translation in the Americas: MT Researchers' Track, pages 40–52, Austin, TX, USA. The Association for Machine Translation in the Americas.