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Most existing methods in binaural sound source localization rely on some kindof aggregation of phase-and level-difference cues in the time-frequency plane.While different ag-gregation schemes exist, they are often heuristic and sufferin adverse noise conditions. In this paper, we introduce the rectified binauralratio as a new feature for sound source local-ization. We show that forGaussian-process point source signals corrupted by stationary Gaussian noise,this ratio follows a complex t-distribution with explicit parameters. This newformulation provides a principled and statistically sound way to aggregatebinaural features in the presence of noise. We subsequently derive two simpleand efficient methods for robust relative transfer function and time-delayestimation. Experiments on heavily corrupted simulated and speech signalsdemonstrate the robustness of the proposed scheme.

Rectified binaural ratio: A complex T-distributed feature for robust sound localization