Everyday life applications heavily depend on successful speech transmission and speech com- munication, to name a few smart home with voice command or in hands-free mobile telephony and speech recognition with machines. In all these applications it is quite important to guarantee a high performance robust to the background noise or reverberation in the room. A pre-processing stage in the form of signal enhancement is unavoidable in order to remove the undesired interfer- ing impact originated from background noise sources. While state-of-the-art technology for speech transmission mainly focuses on filtering the signal in amplitude domain, we aim to push the limits of the achievable performance by extending the enhancement problem to both amplitude and phase parts leading to the new concept of phase-aware signal processing. The contributions in this proposal are in three folds: i) find solutions for estimating phase infor- mation about the desired source signal observed in noise and further utilize it to push the limit of the conventional signal enhancement methods, ii) the second goal of the proposal will be to extend the proposed method to speaker-specific solutions where we have prior knowledge about the identity of the device used in a certain application. This additional knowledge can be exploited for further improvement of the achievable performance, iii) the last goal is to find new quality estimators to reflect how human perceives speech in noise. This will help to evaluate the performance of a signal enhancement stage with a higher correlation with human listening outcomes while avoiding tedious task of conducting subjective listening test.