Building robot voice control training methodology using artificial neural net

Публікація:
Building robot voice control training methodology using artificial neural net

dc.contributor.author	Matarneh, R.
dc.contributor.author	Maksymova, S.
dc.contributor.author	Deineko, Z.
dc.contributor.author	Lyashenko, V.
dc.date.accessioned	2018-06-26T10:11:28Z
dc.date.available	2018-06-26T10:11:28Z
dc.date.issued	2017
dc.description.abstract	The article describes using artificial neural net for speech recognition. This is necessary for the automation of construction work. We selected multi-layer perceptron for separate words recognition tasks. We researcheddifferent forms of hidden layer. And we made a conclusion that for voice commands analysis tasks solution it is expedient to use multi-layer perceptron with linearized functions (the best result was achieved using model with hidden layer with linearized hyperbolic tangent function). We use this experience to train robots in civil engineering.	uk_UA
dc.identifier.citation	Matarneh R., Maksymova S., Deineko Z., Lyashenko V. Building Robot Voice Control Training Methodology Using Artificial Neural Net // International Journal of Civil Engineering and Technology. – 2017. – Vol. 8(10). – P. 523–532.	uk_UA
dc.identifier.issn	0976-6308
dc.identifier.uri	http://openarchive.nure.ua/handle/document/6389
dc.language.iso	en	uk_UA
dc.publisher	IAEME publication	uk_UA
dc.subject	Building Robot	uk_UA
dc.subject	Voice Control	uk_UA
dc.title	Building robot voice control training methodology using artificial neural net	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication