Efficient Search for Interactive Statistical Machine Translation
Abstract
The goal of interactive machine translation
is to improve the productivity of human
translators. An interactive machine
translation system operates as follows:
the automatic system proposes a translation.
Now, the human user has two options:
to accept the suggestion or to correct
it. During the post-editing process,
the human user is assisted by the interactive
system in the following way: the
system suggests an extension of the current
translation prefix. Then, the user either
accepts this extension (completely
or partially) or ignores it. The two most
important factors of such an interactive
system are the quality of the proposed
extensions and the response time. Here,
we will use a fully fledged translation
system to ensure the quality of the proposed
extensions. To achieve fast response
times, we will use word hypotheses
graphs as an efficient search space
representation. We will show results of
our approach on the Verbmobil task and
on the Canadian Hansards task.
is to improve the productivity of human
translators. An interactive machine
translation system operates as follows:
the automatic system proposes a translation.
Now, the human user has two options:
to accept the suggestion or to correct
it. During the post-editing process,
the human user is assisted by the interactive
system in the following way: the
system suggests an extension of the current
translation prefix. Then, the user either
accepts this extension (completely
or partially) or ignores it. The two most
important factors of such an interactive
system are the quality of the proposed
extensions and the response time. Here,
we will use a fully fledged translation
system to ensure the quality of the proposed
extensions. To achieve fast response
times, we will use word hypotheses
graphs as an efficient search space
representation. We will show results of
our approach on the Verbmobil task and
on the Canadian Hansards task.
