• DocumentCode
    2963372
  • Title

    EMG based voice recognition

  • Author

    Kumar, Sanjay ; Kumar, Dinesh Kant ; Alemu, Melaku ; Burry, Mark

  • Author_Institution
    Spatial Inf. Archit. Lab., R. Melbourne Inst. of Technol., Vic., Australia
  • fYear
    2004
  • fDate
    14-17 Dec. 2004
  • Firstpage
    593
  • Lastpage
    597
  • Abstract
    Besides its clinical applications, various researchers have shown that EMG can be utilised in areas such as computer human interface and in developing intelligent prosthetic devices. The paper presents results from a preliminary study. The work describes the outcome in using an artificial neural network (ANN) to recognise and classify human speech based on EMG. The EMG signals were acquired from three articulatory facial muscles. Three subjects were selected and participated in the experiments. Preliminarily, five English vowels were used as recognition variables. The root mean square (RMS) values of the EMG signals were estimated and used as a set of features to feed the ANN. The findings indicate that such a system may have the capacity to recognise and classify speech signals with an accuracy of up to 88%.
  • Keywords
    electromyography; neural nets; parameter estimation; signal classification; speech recognition; ANN; EMG signal RMS values; articulatory facial muscles; artificial neural network; computer human interface; intelligent prosthetic devices; speech classification; speech recognition; voice recognition; vowels; Application software; Artificial intelligence; Artificial neural networks; Computer interfaces; Electromyography; Facial muscles; Humans; Neural prosthesis; Root mean square; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
  • Print_ISBN
    0-7803-8894-1
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2004.1417528
  • Filename
    1417528