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A common characteristics of the computational models of visual attention is they execute the two modes of visual attention (visual exploration and visual search) separately. This makes a visual attention model unsuitable for real-world robotic applications. This paper focuses on integrating visual exploration and visual search in a common framework of visual attention and the challenges resulting from such integration. It proposes a visual attention-oriented speech-based human robot interaction framework which helps a robot to switch back and-forth between the two modes of visual attention. A set of experiments are presented to demonstrate the performance of the proposed framework.