  To achieve human-like behaviour during speech interactions, it is necessary
for a humanoid robot to estimate the location of a human talker. Here, we
present a method to optimize the parameters used for the direction of arrival
(DOA) estimation, while also considering real-time applications for human-robot
interaction scenarios. This method is applied to binaural sound source
localization framework on a humanoid robotic head. Real data is collected and
annotated for this work. Optimizations are performed via a brute force method
and a Bayesian model based method, results are validated and discussed, and
effects on latency for real-time use are also explored.
