Publication detail

Comparison of Feature Performance in Gunshot Detection Depending on Noise Degradation

HRABINA, M. SIGMUND, M.

Original Title

Comparison of Feature Performance in Gunshot Detection Depending on Noise Degradation

Type

conference paper

Language

English

Original Abstract

This paper compares three different features and various feature orders for the purpose of determining the best feature for gunshot detection under adverse noise condition. Compared features cover LPC, LPCC and MFCC with orders from 8 to 30. All features were extracted from sounds with the sound-to-noise ratios 30, 20, 10, and 0 dB. The background noise was simulated by white noise. Experimental results indicate that LPC coefficients are the most efficient features, especially for low noise. On the other hand, MFCC performed well in noisy environments at 10 dB and 20 dB.

Keywords

gunshot detection, feature analysis, linear predictive coding coefficients, cepstrum, noise

Authors

HRABINA, M.; SIGMUND, M.

Released

19. 4. 2017

Location

Brno

ISBN

978-1-5090-4591-4

Book

Proceedings of 27th International Conference Radioelektronika 2017

Pages from

223

Pages to

226

Pages count

4

URL

https://ieeexplore.ieee.org/document/7937601

BibTex

@inproceedings{BUT135464,
  author="Martin {Hrabina} and Milan {Sigmund}",
  title="Comparison of Feature Performance in Gunshot Detection Depending on Noise Degradation",
  booktitle="Proceedings of 27th International Conference Radioelektronika 2017",
  year="2017",
  pages="223--226",
  address="Brno",
  doi="10.1109/RADIOELEK.2017.7937601",
  isbn="978-1-5090-4591-4",
  url="https://ieeexplore.ieee.org/document/7937601"
}