  Machine translation is generally understood as generating one target text
from an input source document. In this paper, we consider a stronger
requirement: to jointly generate two texts so that each output side effectively
depends on the other. As we discuss, such a device serves several practical
purposes, from multi-target machine translation to the generation of controlled
variations of the target text. We present an analysis of possible
implementations of dual decoding, and experiment with four applications.
Viewing the problem from multiple angles allows us to better highlight the
challenges of dual decoding and to also thoroughly analyze the benefits of
generating matched, rather than independent, translations.
