Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft (항공기 1차조종면 제어를 위한 딥러닝 기반 음성인식 비행 제어장치의 구현)

Hwa-La Hur (허화라); Tae-Sun Kim (김태선); Myeong-Chul Park (박명철)

doi:10.9708/jksci.2021.26.09.057

Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2021, 26(9), pp.57-64
DOI : 10.9708/jksci.2021.26.09.057
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : August 25, 2021
Accepted : September 24, 2021
Published : September 30, 2021

Hwa-La Hur ¹, Tae-Sun Kim ¹, Myeong-Chul Park ¹

¹경운대학교

Accredited

ABSTRACT

In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.

KEYWORDS

Speech Recognition, CNN, MFCC, Flight Controller, TensorFlow

Citation status

* References for papers published after 2023 are currently being built.

[journal] M. A. Anusuya / 2009 / Speech Recognition by Machine, A Review / International Journal of Computer Science and Information Security, IJCSIS 6(3) : 181~205

[confproc] Myeong-Chul Park / 2020 / Drone controller using motion imagery brainwave and voice recognition / Proceedings of the Korean Society of Computer Information Conference : 257~258

[confproc] T. N. Sainath / 2013 / Deep convolutional neural networks for LVCSR / 2013 IEEE International Conference on Acoustics, Speech and Signal Processing : 8614~8618

[confproc] Mitra. Vikramjit / 2014 / Evaluating robust features on Deep Neural Networks for speech recognition in noisy and channel mismatched conditions / Proceedings of the Annual Conference of the International Speech Communication Association : 895~899

[confproc] V. Pratap / 2019 / Wav2Letter++: A Fast Open-source Speech Recognition System / IEEE International Conference on Acoustics, Speech and Signal Processing : 6460~6464

[journal] S. Davis / 1980 / Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences / IEEE Transactions on Acoustics, Speech, and Signal Processing / Institute of Electrical and Electronics Engineers (IEEE) 28(4) : 357~366

[other] Warden. Pete / 2018 / Speech Commands : A Dataset for Limited-Vocabulary Speech Recognition / ArXiv Preprint ArXiv:1804.03209

[journal] Ali Bou Nassif / 2019 / Speech Recognition Using Deep Neural Networks: A Systematic Review / IEEE Access / Institute of Electrical and Electronics Engineers (IEEE) 7 : 19143~19165

[journal] 장동열 / 2021 / Integrated System of Mobile Manipulator with Speech Recognition and Deep Learning-based Object Detection / 로봇학회 논문지 / 한국로봇학회 16(3) : 270~275

[journal] 소순원 / 2018 / Development of Age Classification Deep Learning Algorithm Using Korean Speech / 의공학회지 / 대한의용생체공학회 39(2) : 63~68

[journal] Tomasz Rogalski / 2010 / A concept of voice guided general aviation aircraft / Aerospace Science and Technology / Elsevier BV 14(5) : 321~328

[journal] 김성우 / 2013 / A Study on Cockpit Voice Command System for Fighter Aircraft / 한국항공우주학회지 / 한국항공우주학회 41(12) : 1011~1017

[journal] Aziz Siyaev / 2021 / Towards Aircraft Maintenance Metaverse Using Speech Interactions with Virtual Objects in Mixed Reality / Sensors / MDPI AG 21(6) : 2066~

[journal] Yu-Yi Lin / 2021 / A Speech Command Control-Based Recognition System for Dysarthric Patients Based on Deep Learning Technology / Applied Sciences / MDPI AG 11(6) : 2477~

[journal] Ruben Contreras / 2020 / Unmanned Aerial Vehicle Control through Domain-Based Automatic Speech Recognition / Computers / MDPI AG 9(3) : 75~

KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Implementation of Speech Recognition and Flight Controller Based on Deep Learning for Control to Primary Control Surface of Aircraft

ABSTRACT

KEYWORDS

Statistics

Tools

Issue List

Citation status

KCI Citation Counts (1)

REFERENCES (15) * References for papers published after 2023 are currently being built.

Search PDF

Citation

* References for papers published after 2023 are currently being built.