Autors: Pleshkova, S. G., Bekyarski, A. B., Zahariev, Z. T.
Title: Reduced Database for voice commands recognition using cloud technologies, artificial intelligence and deep learning
Keywords: Artificial intelligence and neural networks, Cloud database, Cloud technologies, Natural languages, Speech recognition systems, Voice command

Abstract: Voice commands recognition tasks used limited sets of words in comparison of universal speech recognition systems dedicated to work with the whole set of words of one or more that one natural languages. Today these universal speech recognition systems are usually based on cloud technologies, artificial intelligence and probably on neural networks with deep learning. The main drawback of using these universal speech recognition systems in tasks like voice commands recognition is the need of unnecessary search the limited set of words (a few words of voice commands) in the databases, containing very large set of words of a chosen natural language..



    16th International Conference on Electrical Machines, Drives and Power Systems,6 June 2019 through 8 June 2019, vol. ELMA 2019 -, issue 16, pp. Article number 8771526, 2019, Bulgaria, Institute of Electrical and Electronics Engineers Inc., DOI 10.1109/ELMA.2019.8771526

    Copyright IEEE

    Цитирания (Citation/s):
    1. Marielet Guillermo. Implementation of Automated Annotation through Mask RCNN Object Detection model in CVAT using AWS EC2 Instance - 2020 - в издания, индексирани в Scopus или Web of Science
    2. Dr. K. Karuppasamy.Touch Free Challan Form Filling System using Face Detection,September 2020 DOI: 10.22214/ijraset.2020.31507. International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429 Volume 8 Issue IX Sep 2020- Available at - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus