Computational auditory saliency

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Delmotte, Varinthira Duangudom
Anderson, David V.
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The objective of this dissertation research is to identify sounds that grab a listener's attention. These sounds that draw a person's attention are sounds that are considered salient. The focus here will be on investigating the role of saliency in the auditory attentional process. In order to identify these salient sounds, we have developed a computational auditory saliency model inspired by our understanding of the human auditory system and auditory perception. By identifying salient sounds we can obtain a better understanding of how sounds are processed by the auditory system, and in particular, the key features contributing to sound salience. Additionally, studying the salience of different auditory stimuli can lead to improvements in the performance of current computational models in several different areas, by making use of the information obtained about what stands out perceptually to observers in a particular scene. Auditory saliency also helps to rapidly sort the information present in a complex auditory scene. Since our resources are finite, not all information can be processed equally. We must, therefore, be able to quickly determine the importance of different objects in a scene. Additionally, an immediate response or decision may be required. In order to respond, the observer needs to know the key elements of the scene. The issue of saliency is closely related to many different areas, including scene analysis. The thesis provides a comprehensive look at auditory saliency. It explores the advantages and limitations of using auditory saliency models through different experiments and presents a general computational auditory saliency model that can be used for various applications.
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