3 Citations (Scopus)

Abstract

Research on speech recognition for several languages has been shown significant improvement for seamless interaction between human and robot. In this study, a system to command assistant robot with Indonesian speech recognition using deep neural network (DNN) has been proposed. The DNN architecture created by convolutional neural networks (CNNs), max pooling, and fully connected layers. The experiments performed on a self-constructed dataset with training, validation, and testing data in 0.8:0.1:0.1 ratio. This network built using Keras (TensorFlow Backend) and the result shows 99.43% accuracy on testing data and 89.57% on actual condition.

Original languageEnglish
Title of host publicationProceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages434-438
Number of pages5
ISBN (Electronic)9781728137490
DOIs
Publication statusPublished - Aug 2019
Event2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019 - Surabaya, Indonesia
Duration: 28 Aug 201929 Aug 2019

Publication series

NameProceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019

Conference

Conference2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Country/TerritoryIndonesia
CitySurabaya
Period28/08/1929/08/19

Keywords

  • Indonesian language
  • deep neural network
  • speech recognition

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