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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Format: | Article |
Language: | English |
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Samara National Research University
2023-04-01
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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. |
first_indexed | 2024-03-08T16:28:37Z |
format | Article |
id | doaj.art-c169b0a537a146c28320fcedbdb747c8 |
institution | Directory Open Access Journal |
issn | 0134-2452 2412-6179 |
language | English |
last_indexed | 2024-03-08T16:28:37Z |
publishDate | 2023-04-01 |
publisher | Samara National Research University |
record_format | Article |
series | Компьютерная оптика |
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 |