Detail publikačního výsledku

Optimization of Mel-Frequency Cepstral Coefficients for Automatic Gunshot Detection

HRABINA, M.

Originální název

Optimization of Mel-Frequency Cepstral Coefficients for Automatic Gunshot Detection

Anglický název

Optimization of Mel-Frequency Cepstral Coefficients for Automatic Gunshot Detection

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

Mel-frequency cepstral coefficients (MFCCs) are features widely used in tasks such as sound event detection (SED), speech recognition or other audio processing problems. This paper explores various ways of modification MFCCs in order to achieve optimal detection results for gunshot detection task. The paper focuses especially on frequency scale and bandwidth, number of filter banks and filter bank shape. The final results achieve recognition performance of 98.7 true negative rate (TNR) and 84.8 true positive rate (TPR).

Anglický abstrakt

Mel-frequency cepstral coefficients (MFCCs) are features widely used in tasks such as sound event detection (SED), speech recognition or other audio processing problems. This paper explores various ways of modification MFCCs in order to achieve optimal detection results for gunshot detection task. The paper focuses especially on frequency scale and bandwidth, number of filter banks and filter bank shape. The final results achieve recognition performance of 98.7 true negative rate (TNR) and 84.8 true positive rate (TPR).

Klíčová slova

gunshot detection, mel-frequency cepstral coefficients, optimization

Klíčová slova v angličtině

gunshot detection, mel-frequency cepstral coefficients, optimization

Autoři

HRABINA, M.

Rok RIV

2020

Vydáno

10.09.2019

ISBN

978-80-214-5781-2

Kniha

Proceedings of IEEE Student Branch Conference Mikulov 2019

Strany od

46

Strany do

48

Strany počet

3

BibTex

@inproceedings{BUT159769,
  author="Martin {Hrabina}",
  title="Optimization of Mel-Frequency Cepstral Coefficients for Automatic Gunshot Detection",
  booktitle="Proceedings of IEEE Student Branch Conference Mikulov 2019",
  year="2019",
  pages="46--48",
  isbn="978-80-214-5781-2"
}

Dokumenty

Mikulov2019_Hrabina