Improving the computational complexity and word recognition rate for dysarthria speech using robust frame selection algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU124660" target="_blank" >RIV/00216305:26220/17:PU124660 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1504/IJSISE.2017.10006783" target="_blank" >http://dx.doi.org/10.1504/IJSISE.2017.10006783</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1504/IJSISE.2017.10006783" target="_blank" >10.1504/IJSISE.2017.10006783</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Improving the computational complexity and word recognition rate for dysarthria speech using robust frame selection algorithm

Popis výsledku v původním jazyce

Dysarthria is a speech syndrome caused by the neurological damage in motor speech glands. In this paper, a robust frame selection algorithm has been employed to recognise the dysarthria speech with less time consumption. This algorithm determines the more informative frames which in turn reduce the size of feature matrix used for recognising the speech. This method results in a significant reduction in computational complexity without compromising with the word recognition rate (WRR) which may support a real time application. The amalgamation of four prosodic features: Mel frequency cepstral coefficients (MFCCs), Log of energy per frame, differential MFCCs and double differential MFCCs has been used for training and testing the Hidden Markov Models (HMMs) for speech recognition. Several try-outs were performed on the high, medium and low intelligibility audio clips with a vocabulary size of 29 isolated words. The time complexity of the whole system is reduced up to 54.8% with respect to the time taken by the system without implementing RFS. The proposed scheme is gender, speaker and age independent

Název v anglickém jazyce

Improving the computational complexity and word recognition rate for dysarthria speech using robust frame selection algorithm

Popis výsledku anglicky

Dysarthria is a speech syndrome caused by the neurological damage in motor speech glands. In this paper, a robust frame selection algorithm has been employed to recognise the dysarthria speech with less time consumption. This algorithm determines the more informative frames which in turn reduce the size of feature matrix used for recognising the speech. This method results in a significant reduction in computational complexity without compromising with the word recognition rate (WRR) which may support a real time application. The amalgamation of four prosodic features: Mel frequency cepstral coefficients (MFCCs), Log of energy per frame, differential MFCCs and double differential MFCCs has been used for training and testing the Hidden Markov Models (HMMs) for speech recognition. Several try-outs were performed on the high, medium and low intelligibility audio clips with a vocabulary size of 29 isolated words. The time complexity of the whole system is reduced up to 54.8% with respect to the time taken by the system without implementing RFS. The proposed scheme is gender, speaker and age independent

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/LO1401" target="_blank" >LO1401: Interdisciplinární výzkum bezdrátových technologií</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

International Journal of Signal and Imaging Systems Engineering

ISSN

1748-0698

e-ISSN

1748-0701

Svazek periodika

10

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

136-145

Kód UT WoS článku

000416610700003

EID výsledku v databázi Scopus

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