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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>

  • Continuities

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

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Signal and Imaging Systems Engineering

  • ISSN

    1748-0698

  • e-ISSN

    1748-0701

  • Volume of the periodical

    10

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    10

  • Pages from-to

    136-145

  • UT code for WoS article

    000416610700003

  • EID of the result in the Scopus database