A new binaural signal modification system is proposed based on the Binaural Cue Adapta-
tion (BCA ) algorithm and it is evaluated with existing BCA algorithms. The BCA algorithm
dynamically adjusts binaural signals according to the listener’s head movements using a head
tracker. This is done by splitting the signal into two components.

The system under evaluation proposed in this thesis considers the reverberation as temporally
correlated with the source signal, in contrast to the baseline BCA system. With the implemen-
tation of the Weighted Prediction Error ( WPE ) dereverberation algorithm, the BCA system
has a component that explicitly removes reverberation. In addition, an online implementation
of the BCA system is presented for evaluation purposes.

The three systems presented in this thesis - the baseline BCA system, the proposed offline
BCA system and the online BCA system - were evaluated using a MUSHRA listening test.
Based on questions about basic audio quality, source direction and reverberation perception,
15 participants evaluated the three systems for 4 different scenarios.
A statistically significant difference between the evaluated systems could not be found in terms
of source localisation quality. Statistically significant differences were found in the ratings
of basic audio quality and the perception of reverberation, with the system using an online
implementation of WPE performing best.