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Unmanned Aerial Vehicle Control through Domain-Based Automatic Speech Recognition

1
Escuela de Ingeniería, Universidad Central de Chile, Santiago 8330601, Chile
2
Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife 50720-001, Brazil
3
School of Information Technology, Deakin University, Geelong 3220, Australia
*
Authors to whom correspondence should be addressed.
Computers 2020, 9(3), 75; https://doi.org/10.3390/computers9030075
Received: 5 August 2020 / Revised: 17 September 2020 / Accepted: 17 September 2020 / Published: 19 September 2020
(This article belongs to the Special Issue Feature Paper in Computers)
Currently, unmanned aerial vehicles, such as drones, are becoming a part of our lives and extend to many areas of society, including the industrialized world. A common alternative for controlling the movements and actions of the drone is through unwired tactile interfaces, for which different remote control devices are used. However, control through such devices is not a natural, human-like communication interface, which sometimes is difficult to master for some users. In this research, we experimented with a domain-based speech recognition architecture to effectively control an unmanned aerial vehicle such as a drone. The drone control was performed in a more natural, human-like way to communicate the instructions. Moreover, we implemented an algorithm for command interpretation using both Spanish and English languages, as well as to control the movements of the drone in a simulated domestic environment. We conducted experiments involving participants giving voice commands to the drone in both languages in order to compare the effectiveness of each, considering the mother tongue of the participants in the experiment. Additionally, different levels of distortion were applied to the voice commands to test the proposed approach when it encountered noisy input signals. The results obtained showed that the unmanned aerial vehicle was capable of interpreting user voice instructions. Speech-to-action recognition improved for both languages with phoneme matching in comparison to only using the cloud-based algorithm without domain-based instructions. Using raw audio inputs, the cloud-based approach achieves 74.81% and 97.04% accuracy for English and Spanish instructions, respectively. However, with our phoneme matching approach the results are improved, yielding 93.33% accuracy for English and 100.00% accuracy for Spanish. View Full-Text
Keywords: drone control; automatic speech recognition; robot simulator drone control; automatic speech recognition; robot simulator
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Contreras, R.; Ayala, A.; Cruz, F. Unmanned Aerial Vehicle Control through Domain-Based Automatic Speech Recognition. Computers 2020, 9, 75.

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