Add to ORKGThis paper reports on the ongoing work focused on domain adaptation of statistical machine translation using domain-specific data obtained by domain-focused web crawling. We present a strategy for crawling monolingual and parallel data and their exploitation for testing, language modelling, and system tuning in a phrase--based machine translation framework. The proposed approach is evaluated on the domains of Natural Environment and Labour Legislation and two language pairs: English–French and English–Greek
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
In recent years the performance of SMT increased in domains with enough train-ing data. But under re...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) b...
The Author(s) 2015. This article is published with open access at Springerlink.com Abstract In this ...
We tackle the problem of domain adapta-tion of Statistical Machine Translation by exploiting domain-...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Globalization suddenly brings many people from different country to interact with each other, requir...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
In recent years the performance of SMT increased in domains with enough train-ing data. But under re...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
This paper reports on the ongoing work focused on domain adaptation of statistical machine translati...
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) b...
The Author(s) 2015. This article is published with open access at Springerlink.com Abstract In this ...
We tackle the problem of domain adapta-tion of Statistical Machine Translation by exploiting domain-...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Globalization suddenly brings many people from different country to interact with each other, requir...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
In recent years the performance of SMT increased in domains with enough train-ing data. But under re...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...