the EMNLP-2015 Workshop on Statistical Machine Translation.
The text for all the test sets will be drawn from news articles. Participants may submit translations for any or all of the language directions. In addition to the common test sets the conference organizers will provide optional training resources.
Parallel corpora (including in-domain training data) are available. Evaluation will be carried out both automatically and manually. See detailed information about the task.
Parallel corpora will be available for the above language pairs but also monoligual corpora for each of the four languages. Evaluation will be carried out both automatically and manually.
In this second edition of the task, the evaluation will focus on one language pair (English-German), measuring systems' capability to reduce the distance (HTER) that separates an automatic translation from its human-revised version approved for publication. This edition will focus on IT domain data, and will provide post-editions (of MT output) collected from professional translators.
This task will assess your team's ability to optimize the parameters of a given hierarchical MT system (Moses).
This is a new task where participants are requested to generate a description for an image in a target language, given the image itself and one or more descriptions in a different (source) language.
Submissions will consist of regular full papers of 6-10 pages, plus additional pages for references, formatted following the ACL 2016 guidelines. In addition, shared task participants will be invited to submit short papers (4-6 pages) describing their systems or their evaluation metrics. Both submission and review processes will be handled electronically. Note that regular papers must be anonymized, while system descriptions do not need to be.
We encourage individuals who are submitting research papers to evaluate their approaches using the training resources provided by this conference and past workshops, so that their experiments can be repeated by others using these publicly available corpora.