Gunshot Recognition using Low Level Features in the Time Domain
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Date
2018-04-19
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Mark
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IEEE
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Abstract
This paper explores the possibility of using scarcely used time-domain features for the task of gunshot recognition. A set of 11 features derived from temporal characteristics (waveform) of signals is calculated from a mixed dataset of gunshots and non-gunshots. The features leverage the impulsive nature of gunshots and their dissimilarity to other, especially more stationary signals. The paper includes a description of feature extraction, distribution of features and their recognition performance on a selected audio dataset. A subset achieves promising results in comparison with more frequently used spectral-domain features. This makes them a valuable addition to other frequently used features, especially for tasks of impulsive sound recognition.
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Citation
Proceedings of 28th International Conference Radioelektronika 2018. 2018, p. 1-5.
https://ieeexplore.ieee.org/document/8376372/
https://ieeexplore.ieee.org/document/8376372/
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Peer-reviewed
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Accepted version
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en