Utilizing MFCC for Voice Intensity Determination

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F10%3APU88290" target="_blank" >RIV/00216305:26220/10:PU88290 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
Utilizing MFCC for Voice Intensity Determination
Popis výsledku v původním jazyce
This paper aims to classify speech signals according to their intensities into 3 groups (silent speech, normal speech and very loud speech). In this work, we have used a number of speech recordings, which were stored in a WAV format. These recordings aredivided into groups with three different intensities, with each of them at three different distances from the point of entry (microphone). Mel Frequency Cepstral Coefficients and k-Nearest Neighbor classifier based algorithm was tested and implemented in Matlab environment. The intensity classification accuracy achieved was about 85%.
Název v anglickém jazyce
Utilizing MFCC for Voice Intensity Determination
Popis výsledku anglicky
This paper aims to classify speech signals according to their intensities into 3 groups (silent speech, normal speech and very loud speech). In this work, we have used a number of speech recordings, which were stored in a WAV format. These recordings aredivided into groups with three different intensities, with each of them at three different distances from the point of entry (microphone). Mel Frequency Cepstral Coefficients and k-Nearest Neighbor classifier based algorithm was tested and implemented in Matlab environment. The intensity classification accuracy achieved was about 85%.

Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
JA - Elektronika a optoelektronika, elektrotechnika
OECD FORD obor
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Rok uplatnění
2010
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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