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Improving Acoustic Detection and Classification in Mobile and Embedded Platforms: Poster Abstract

Sound detection and classification are critical in many acoustic-based applications. Existing works generally focus on discovering new features and classifiers to improve detection. However, in many scenarios the presence of other sounds may hinder the performance of these sound classifiers. In this work, we take a sound filtering and enhancement approach to improve sound detection for mobile and embedded applications, regardless of the type of detector used.