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    <abstract>This paper compares techniques to combine diverse parallel corpora for domain-specific phrase-based SMT system training. We address a common scenario where little in-domain data is available for the task, but where large background models exist for the same language pair. In particular, we focus on phrase table fill-up: a method that effectively exploits background knowledge to improve model coverage, while preserving the more reliable information coming from the in-domain corpus. We present experiments on an emerging transcribed speech translation task – the TED talks. While performing similarly in terms of BLEU and NIST scores to the popular log-linear and linear interpolation techniques, filled-up translation models are more compact and easy to tune by minimum error training.</abstract>
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%0 Conference Proceedings
%T Fill-up versus interpolation methods for phrase-based SMT adaptation
%A Bisazza, Arianna
%A Ruiz, Nick
%A Federico, Marcello
%Y Federico, Marcello
%Y Hwang, Mei-Yuh
%Y Rödder, Margit
%Y Stüker, Sebastian
%S Proceedings of the 8th International Workshop on Spoken Language Translation: Evaluation Campaign
%D 2011
%8 dec 8 9
%C San Francisco, California
%F bisazza-etal-2011-fill
%X This paper compares techniques to combine diverse parallel corpora for domain-specific phrase-based SMT system training. We address a common scenario where little in-domain data is available for the task, but where large background models exist for the same language pair. In particular, we focus on phrase table fill-up: a method that effectively exploits background knowledge to improve model coverage, while preserving the more reliable information coming from the in-domain corpus. We present experiments on an emerging transcribed speech translation task – the TED talks. While performing similarly in terms of BLEU and NIST scores to the popular log-linear and linear interpolation techniques, filled-up translation models are more compact and easy to tune by minimum error training.
%U https://aclanthology.org/2011.iwslt-evaluation.18/
%P 136-143

Markdown (Informal)

[Fill-up versus interpolation methods for phrase-based SMT adaptation](https://aclanthology.org/2011.iwslt-evaluation.18/) (Bisazza et al., IWSLT 2011)

• Fill-up versus interpolation methods for phrase-based SMT adaptation (Bisazza et al., IWSLT 2011)

ACL

• Arianna Bisazza, Nick Ruiz, and Marcello Federico. 2011. Fill-up versus interpolation methods for phrase-based SMT adaptation. In Proceedings of the 8th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 136–143, San Francisco, California.