Multiresolution alignment for multiple unsynchronized audio sequences using sequential Monte Carlo samplers

It is increasingly more common that an occasion is recorded by multiple individuals with the proliferation of recording devices such as smart phones. When properly aligned, these recordings may provide several audio and visual perspectives to a scene which leads to several applications in restoring, remastering and remixing frameworks in various fields. In this work, we propose a multiresolution alignment algorithm for aligning multiple unsynchronized audio sequences using Sequential Monte Carlo samplers. We employ a model based approach and a score function analogous to similarity based methods. The optimum alignments are obtained in a course to fine structure with multiresolution sampling and a heuristic sequential search method. The proposed method is evaluated with a real-life dataset from Jiku Mobile Video Datasets. The simulation results suggest that our method is competitive with the baseline methods in terms of accuracy with suitable choice of parameters.