16 research outputs found
Untersuchungen über Beziehungen zwischen Reaktionsempfindlichkeit und Molekülgröße bei organischen Reagenzien
Findings of the 2014 Workshop on Statistical Machine Translation
This paper presents the results of the WMT14 shared tasks, which included a standard news translation task, a separate medical translation task, a task for run-time estimation of machine translation quality, and a metrics task. This year, 143 machine translation systems from 23 institutions were submitted to the ten translation directions in the standard translation task. An additional 6 anonymized systems were included, and were then evaluated both automatically and manually. The quality estimation task had four subtasks, with a total of 10 teams, submitting 57 entrie
Domain adaptation of statistical machine translation with domain-focused web crawling
In this paper, we tackle the problem of domain adaptation of statistical machine
translation (SMT) by exploiting domain-specific data acquired by domain-focused crawling
of text from the World Wide Web. We design and empirically evaluate a procedure for auto-
matic acquisition of monolingual and parallel text and their exploitation for system training,
tuning, and testing in a phrase-based SMT framework. We present a strategy for using such
resources depending on their availability and quantity supported by results of a large-scale
evaluation carried out for the domains of environment and labour legislation, two language
pairs (English–French and English–Greek) and in both directions: into and from English.
In general, MT systems trained and tuned on a general domain perform poorly on specific
domains and we show that such systems can be adapted successfully by retuning model
parameters using small amounts of parallel in-domain data, and may be further improved
by using additional monolingual and parallel training data for adaptation of language and
translation models. The average observed improvement in BLEU achieved is substantial at
15.30 points absolute