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Títol: The Method of Commands Identification to Voice Control of the Electric Wheelchair
Autor: Dozorskyi, Vasil
Dediv, Iryna
Sverstiuk, Sofiia
Nykytyuk, Vyacheslav
Karnaukhov, Andrii
Bibliographic description (Ukraine): Dozorskyi V., Dediv I., Sverstiuk S., Nykytyuk V., Karnaukhov A. The Method of Commands Identification to Voice Control of the Electric Wheelchair. Proceedings of the 1st International Workshop on Computer Information Technologies in Industry 4.0 (CITI 2023). CEUR Workshop Proceedings. Ternopil, Ukraine, June 14-16, 2023. P.233-240. ISSN 1613-0073.CEUR Workshop Proceedings. Ternopil, Ukraine
Conference/Event: The 1st International Workshop on «Computer Information Technologies in Industry 4.0» (CITI-2023)
Data de publicació: 14-de -2023
Submitted date: 31-d’o-2023
Date of entry: 31-d’o-2023
Editorial: CEUR Workshop Proceedings
Country (code): UA
Place of the edition/event: CEUR Workshop Proceedings. Ternopil, Ukraine
Paraules clau: Electric wheelchair
voice control
sliding window
main tone frequency
Page range: 233-240
Resum: The paper shows the relevance of the task of improving the electric wheelchair control system for patients with lost or functionally limited upper limbs. A method of indirect control using voice commands is proposed. At the same time, the biometric principle is used, according to which, in the process of voice signal analysis, signs that are biometric parameters of the patient's speech are identified to prevent the operation of the control system when registering similar commands from outsiders. The main such sign is the value of the main tone frequency. To process voice signals in order to identify the four main control commands, namely forward, backward, left and right, the sliding window method is used, within which the presence of signs of the main tone is evaluated. For a specific person, this value will be individual and present only in those parts of the voice signal that correspond to vowels and consonant vocalized sounds. In this way, it is possible to segment the voice signal into such areas and identify individual voice commands based on pre-set durations of these areas. A threshold function is also used for this, which takes a certain value when the main tone frequency is present in the voice signal structure within each implementation of the sliding window and is equal to zero when there are no signs of this frequency. At the same time, it became possible to identify individual commands with higher accuracy.
Content: Abstract; 1. Introduction; 2. Materials and Methods; 3. Experiment and Results; 4. Conclusion; 5. References.
URI: http://elartu.tntu.edu.ua/handle/lib/42705
ISBN: 1613-0073
Copyright owner: © Vasil Dozorskyi, Iryna Dediv, Sofiia Sverstiuk, Vyacheslav Nykytyuk, Andrii Karnaukhov
References (International): [1] World Health Organization. URL: https://www.who.int/
[2] State Statistics Service of Ukraine. URL: https://www.ukrstat.gov.ua/
[3] National Assembly of People with Disabilities of Ukraine. URL: https://www.facebook.com/vgonaiu/posts/1709214279269040/?locale=hi_IN
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Content type: Conference Abstract
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