Modern automatic recognition technologies for visual communication tools

Communication refers to a wide range of different behaviors and activities aimed at handing over information. The communication process includes verbal, paraverbal and non-verbal components, conveying the informational part of a message and its emotional part respectively. A complex analysis of all...

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Main Authors: V.O. Yachnaya, V.R. Lutsiv, R.O. Malashin
Format: Article
Language:English
Published: Samara National Research University 2023-04-01
Series:Компьютерная оптика
Subjects:
Online Access:https://computeroptics.ru/eng/KO/Annot/KO47-2/470212e.html
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author V.O. Yachnaya
V.R. Lutsiv
R.O. Malashin
author_facet V.O. Yachnaya
V.R. Lutsiv
R.O. Malashin
author_sort V.O. Yachnaya
collection DOAJ
description Communication refers to a wide range of different behaviors and activities aimed at handing over information. The communication process includes verbal, paraverbal and non-verbal components, conveying the informational part of a message and its emotional part respectively. A complex analysis of all communication components makes it possible to evaluate not only the content, but also the situational context of what is being said, as well as to identify additional factors inherent in the mental and somatic state of the speaker. There are several methods of conveying a verbal message, among which are oral and gestural speech (such as the sign language and fingerspelling). Various forms of communication can be contained in multiple data transmission channels, such as audio or video channels. The review is concerned with video data analysis systems, as the audio channel is incapable of non-verbal components transmission that contribute supplemental details. The article analyzes databases of static and dynamic images and systems, developed to recognize the verbal component conveyed by oral and gestural speech, as well as systems that evaluate paraverbal and non-verbal components of communication. Challenges of designing such databases and systems are specified. Prospective directions in complex analysis of all communication components and its combinations for the most complete evaluation of messages are defined.
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spelling doaj.art-c169b0a537a146c28320fcedbdb747c82024-01-06T11:14:55ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792023-04-0147228730510.18287/2412-6179-CO-1154Modern automatic recognition technologies for visual communication toolsV.O. Yachnaya0V.R. Lutsiv1R.O. Malashin2Saint-Petersburg State University of Aerospace Instrumentation; Pavlov Institute of PhysiologySaint-Petersburg State University of Aerospace InstrumentationSaint-Petersburg State University of Aerospace Instrumentation; Pavlov Institute of PhysiologyCommunication refers to a wide range of different behaviors and activities aimed at handing over information. The communication process includes verbal, paraverbal and non-verbal components, conveying the informational part of a message and its emotional part respectively. A complex analysis of all communication components makes it possible to evaluate not only the content, but also the situational context of what is being said, as well as to identify additional factors inherent in the mental and somatic state of the speaker. There are several methods of conveying a verbal message, among which are oral and gestural speech (such as the sign language and fingerspelling). Various forms of communication can be contained in multiple data transmission channels, such as audio or video channels. The review is concerned with video data analysis systems, as the audio channel is incapable of non-verbal components transmission that contribute supplemental details. The article analyzes databases of static and dynamic images and systems, developed to recognize the verbal component conveyed by oral and gestural speech, as well as systems that evaluate paraverbal and non-verbal components of communication. Challenges of designing such databases and systems are specified. Prospective directions in complex analysis of all communication components and its combinations for the most complete evaluation of messages are defined.https://computeroptics.ru/eng/KO/Annot/KO47-2/470212e.htmlvisual speech recognitionsign language recognitionaffective computingcomputer visionneural networks
spellingShingle V.O. Yachnaya
V.R. Lutsiv
R.O. Malashin
Modern automatic recognition technologies for visual communication tools
Компьютерная оптика
visual speech recognition
sign language recognition
affective computing
computer vision
neural networks
title Modern automatic recognition technologies for visual communication tools
title_full Modern automatic recognition technologies for visual communication tools
title_fullStr Modern automatic recognition technologies for visual communication tools
title_full_unstemmed Modern automatic recognition technologies for visual communication tools
title_short Modern automatic recognition technologies for visual communication tools
title_sort modern automatic recognition technologies for visual communication tools
topic visual speech recognition
sign language recognition
affective computing
computer vision
neural networks
url https://computeroptics.ru/eng/KO/Annot/KO47-2/470212e.html
work_keys_str_mv AT voyachnaya modernautomaticrecognitiontechnologiesforvisualcommunicationtools
AT vrlutsiv modernautomaticrecognitiontechnologiesforvisualcommunicationtools
AT romalashin modernautomaticrecognitiontechnologiesforvisualcommunicationtools