Voice Source Localization processing needs specific response time(performance) due to the efficiency. Then improving this performance by applying a uniform parallel processing architecture or using a high performance single processing unit would not be efficient. In this case, the pipeline signal processing is required and this way would be more efficient. To get performance efficeint pipeline structure, High level synthesis(HLS) of a pipeline signal processing can be applied. In order to apply HLS, it is needed to understand the main properties of the high level synthesis methods by focusing to the pipeline systems. Then, Initial data flow graph representation is constructed from the algorithm of the voice source localization. To generate some proper segmentations of the initial data flow graph, the Chaco graph decomposition software is applyed. Each proper segmentations is evaluated regarding the effect of the applied decomposing algorithms and the number of segments. Based on the evaluation, at least two benificial sementations are selected. Selected segmentations are applyed to high level synthesis tool PIPE as input data flow. By high level synthesis tool PIPE, the cost versus restart time diagram for each selected segmentation is generated. The restart time is given as initialization interval. And then at least two advantageous restart times for each selected segmentation is defined and the multiprocessing structurer are determined respectively. The multiprocessing structures are evaluated and compared with those given from other work. After then proper implementations (hardware or software) for each processing unit in each structure are suggested. Finally, in order to evaluate the effect of decomposition, above steps are applied to the initial data flow graph without segmentation as input in high level synthesis tool PIPE as well.