  We consider speech enhancement for signals picked up in one noisy environment
that must be rendered to a listener in another noisy environment. For both
far-end noise reduction and near-end listening enhancement, it has been shown
that excessive focus on noise suppression or intelligibility maximization may
lead to excessive speech distortions and quality degradations in favorable
noise conditions, where intelligibility is already at ceiling level. Recently
[1,2] propose to remedy this with a minimum processing framework that either
reduces noise or enhances listening a minimum amount given that a certain
intelligibility criterion is still satisfied Additionally, it has been shown
that joint consideration of both environments improves speech enhancement
performance. In this paper, we formulate a joint far- and near-end minimum
processing framework, that improves intelligibility while limiting speech
distortions in favorable noise conditions. We provide closed-form solutions to
specific boundary scenarios and investigate performance for the general case
using numerical optimization. We also show concatenating existing minimum
processing far- and near-end enhancement methods preserves the effects of the
initial methods. Results show that the joint optimization can further improve
performance compared to the concatenated approach.
