Université Blida 1

Multilingual voice recognition using deep learning for human-drone interaction

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dc.contributor.author Mebarkia, Nihad
dc.contributor.author Kacel, Yasmine; Choutri, Kheireddine (promoteur); Lagha, Mohand (promoteur)
dc.date.accessioned 2021-11-25T09:09:32Z
dc.date.available 2021-11-25T09:09:32Z
dc.date.issued 2021
dc.identifier.uri http://di.univ-blida.dz:8080/jspui/handle/123456789/13156
dc.description Mémoire de Master option Avionique .-Numéro de Thèse 050/2021 fr_FR
dc.description.abstract Over the past several years, human-drone interaction have got an important part from the scientific researchs. When interacting with a drone, humans take on many responsibilities. Their role is determined by the drone’s application and the amount of autonomy. The purpose of this work is to control the movement of the unmanned aerial vehicle (UAV) using a multilingual speech recognition system. For that, a deep neural network (DNN) is trained to recognize the user’s speech from many languages and then generate the desired control command. We conducted experiments involving participants giving voice commands in order to compare the effectivencess of each database. Hardware implementation of the designed system proof its high accuracy recognition and control simplicity. fr_FR
dc.language.iso en fr_FR
dc.publisher Université Blida 01 fr_FR
dc.subject Speech recognition; DNN; UAV, ; Control; Human-Drone Interaction fr_FR
dc.title Multilingual voice recognition using deep learning for human-drone interaction fr_FR
dc.type Thesis fr_FR


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