2016/09/30 by Antoine Deleforge, Deleforge, Antoine, Florence Forbes +1
Computer Science · Engineering · #Advanced Adaptive Filtering Techniques #Applications (stat.AP) #FOS: Computer and information sciences #Music and Audio Processing #Sound (cs.SD) #Speech and Audio Processing
paper · pdf · doi:10.48550/arxiv.1609.09743
openalex publication_date 2016/09/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Most existing methods in binaural sound source localization rely on some kind\nof aggregation of phase-and level-difference cues in the time-frequency plane.\nWhile different ag-gregation schemes exist, they are often heuristic and suffer\nin adverse noise conditions. In this paper, we introduce the rectified binaural\nratio as a new feature for sound source local-ization. We show that for\nGaussian-process point source signals corrupted by stationary Gaussian noise,\nthis ratio follows a complex t-distribution with explicit parameters. This new\nformulation provides a principled and statistically sound way to aggregate\nbinaural features in the presence of noise. We subsequently derive two simple\nand efficient methods for robust relative transfer function and time-delay\nestimation. Experiments on heavily corrupted simulated and speech signals\ndemonstrate the robustness of the proposed scheme.\n