Intelligent human-machine voice communication system

Title:

Intelligent human-machine voice communication system

Creator:

Majewski, Maciej and Kacalak, Wojciech

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:86bda7f4-0597-4fe8-be9a-1ec2d95393f5
uuid:86bda7f4-0597-4fe8-be9a-1ec2d95393f5

Subject:

speech, voice communication, command recognition, artificial intelligence, artificial neural networks, and human machine interface

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In the future, speech unquestionably will become the primary means of communication between humans and machines. New applications of artificial neural networks are capable of recognizing human speech and analyze the meaning of the recognized text. The condition of the effectiveness of two-way human-machine voice communication is to apply the mechanisms of command verification and correctness. In this paper there is a review of the selected issues on recognition and safety estimations of voice commands in natural language given by the operator of the technological device. A view is offered of the complexity of the recognition process of the operator‘s words and commands using neural networks made of a few layers of neurons. There is also an intelligent system of two-way voice communication between the technological device and the operator presented, which consists of the intelligent mechanism of operator identification, word and command recognition, command syntax and result analysis, command safety assessment, technological process supervision as well as operator reaction assessment. The paper presents research results of speech recognition and automatic command recognition as well as command safety estimation with artificial neural networks. and Obsahuje seznam literatury

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

193-200

Source:

Engineering mechanics: international journal for theoretical and applied mechanics | 2005 Volume:12 | Number:3

Harvested from:

CDK

Metadata only:

false