Speaker Verification Using Autoregressive Spectrum of Speech Signal in Composite Vector Stochastic Processes Model Representation
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F19%3A39915277" target="_blank" >RIV/00216275:25530/19:39915277 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.journalimcms.org/special_issue/speaker-verification-using-autoregressive-spectrum-of-speech-signal-in-composite-vector-stochastic-processes-model-representation/" target="_blank" >http://www.journalimcms.org/special_issue/speaker-verification-using-autoregressive-spectrum-of-speech-signal-in-composite-vector-stochastic-processes-model-representation/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.26782/jmcms.spl.4/2019.11.00018" target="_blank" >10.26782/jmcms.spl.4/2019.11.00018</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Speaker Verification Using Autoregressive Spectrum of Speech Signal in Composite Vector Stochastic Processes Model Representation
Popis výsledku v původním jazyce
This paper deals with the speaker verification system similar to a fingerprint or an eye scanner. For these purpose a long-term words' model and its spectral characteristics were used. The speaker verification method uses the word's sound parametric spectrum factorization in composite vector stochastic process representation based on the multiplicative autoregressive model. The developed method enables to receive the words' features with stable characteristics for the same speaker and differ for different speakers. During the training phase speaker's etalon frequencies has to be estimated for a pronounced word repeated several times. In the verification phase a speaker pronouncing the same word, word's frequencies are estimated and compared with the etalon frequencies database to find the best match or his deny. The results presented in the paper showed the high correct identification probability.
Název v anglickém jazyce
Speaker Verification Using Autoregressive Spectrum of Speech Signal in Composite Vector Stochastic Processes Model Representation
Popis výsledku anglicky
This paper deals with the speaker verification system similar to a fingerprint or an eye scanner. For these purpose a long-term words' model and its spectral characteristics were used. The speaker verification method uses the word's sound parametric spectrum factorization in composite vector stochastic process representation based on the multiplicative autoregressive model. The developed method enables to receive the words' features with stable characteristics for the same speaker and differ for different speakers. During the training phase speaker's etalon frequencies has to be estimated for a pronounced word repeated several times. In the verification phase a speaker pronouncing the same word, word's frequencies are estimated and compared with the etalon frequencies database to find the best match or his deny. The results presented in the paper showed the high correct identification probability.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Mechanics of Continua and Mathematical Sciences
ISSN
2454-7190
e-ISSN
—
Svazek periodika
No. 4
Číslo periodika v rámci svazku
11 2019
Stát vydavatele periodika
IN - Indická republika
Počet stran výsledku
13
Strana od-do
178-190
Kód UT WoS článku
000495435200018
EID výsledku v databázi Scopus
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