Cepstral Coefficients Effectiveness for Gunshot Classifying

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00374531" target="_blank" >RIV/68407700:21230/24:00374531 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1088/1361-6501/ad3c5d" target="_blank" >https://doi.org/10.1088/1361-6501/ad3c5d</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1361-6501/ad3c5d" target="_blank" >10.1088/1361-6501/ad3c5d</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cepstral Coefficients Effectiveness for Gunshot Classifying

Popis výsledku v původním jazyce

This paper analyses the efficiency of various frequency cepstral coefficients (fCC) in a non-speech application, specifically in classifying acoustic impulse events - gunshots. There are various methods for such event identification available. The majority of these methods are based on time or frequency domain algorithms. However, both of these domains have their limitations and disadvantages. In this article, an fCC, combining the advantages of both frequency and time domains, is presented and analyzed. These originally speech features showed potential not only in speech-related applications but also in other acoustic applications. The comparison of the classification efficiency based on features obtained using four different fCC, namely Mel-frequency Cepstral Coefficients (MFCC), Inverse Mel-frequency Cepstral Coefficients (IMFCC), Linear-frequency Cepstral Coefficients (LFCC), and Gammatone-frequency Cepstral Coefficients (GTCC) is presented. An optimal frame length for an fCC calculation is also explored. Various gunshots from short guns and rifle guns of different calibers and multiple acoustic impulse events, similar to the gunshots, to represent false alarms are used. More than six hundred acoustic events records have been acquired and used for training and validation of two designed classifiers, Support Vector Machine, and Neural Network. Accuracy, Recall and Matthew's correlation coefficient measure the classification success rate. The results reveal the superiority of GFCC to other analyzed methods.

Název v anglickém jazyce

Cepstral Coefficients Effectiveness for Gunshot Classifying

Popis výsledku anglicky

This paper analyses the efficiency of various frequency cepstral coefficients (fCC) in a non-speech application, specifically in classifying acoustic impulse events - gunshots. There are various methods for such event identification available. The majority of these methods are based on time or frequency domain algorithms. However, both of these domains have their limitations and disadvantages. In this article, an fCC, combining the advantages of both frequency and time domains, is presented and analyzed. These originally speech features showed potential not only in speech-related applications but also in other acoustic applications. The comparison of the classification efficiency based on features obtained using four different fCC, namely Mel-frequency Cepstral Coefficients (MFCC), Inverse Mel-frequency Cepstral Coefficients (IMFCC), Linear-frequency Cepstral Coefficients (LFCC), and Gammatone-frequency Cepstral Coefficients (GTCC) is presented. An optimal frame length for an fCC calculation is also explored. Various gunshots from short guns and rifle guns of different calibers and multiple acoustic impulse events, similar to the gunshots, to represent false alarms are used. More than six hundred acoustic events records have been acquired and used for training and validation of two designed classifiers, Support Vector Machine, and Neural Network. Accuracy, Recall and Matthew's correlation coefficient measure the classification success rate. The results reveal the superiority of GFCC to other analyzed methods.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Measurement Science and Technology

ISSN

0957-0233

e-ISSN

1361-6501

Svazek periodika

35

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

11

Strana od-do

1-11

Kód UT WoS článku

001204907200001

EID výsledku v databázi Scopus

2-s2.0-85190943127