Speech Recognition Using Convolutional Neural Networks

  • Authors

    • D. Nagajyothi
    • P. Siddaiah
    2018-09-25
    https://doi.org/10.14419/ijet.v7i4.6.20449
  • Neural Networks (NN), Convolutional Neural Networks(CNN).

  • Abstract

    Automatic speech recognition (ASR) is the process of converting the vocal speech signals into text using transcripts. In the present era of computer revolution, the ASR plays a major role in enhancing the user experience, in a natural way, while communicating with the machines. It rules out the use of traditional devices like keyboard and mouse, and the user can perform an endless array of applications like controlling of devices and interaction with customer care. In this paper, an ASR based Airport enquiry system is presented. The system has been developed natively for telugu language. The database is created based on the most frequently asked questions in an airport enquiry. Because of its high performance, Convolutional Neural Network (CNN) has been used for training and testing of the database. The salient feature of weight connectivity, local connectivity and polling result is a through training of the system, thus resulting in a superior testing performance. Experiments performed on wideband speech signals results in significant improvement in the performance of the system in comparison to the traditional techniques.

     

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  • How to Cite

    Nagajyothi, D., & Siddaiah, P. (2018). Speech Recognition Using Convolutional Neural Networks. International Journal of Engineering & Technology, 7(4.6), 133-137. https://doi.org/10.14419/ijet.v7i4.6.20449

    Received date: 2018-09-29

    Accepted date: 2018-09-29

    Published date: 2018-09-25