Modern automatic recognition technologies for visual communication tools

被引:0
|
作者
Yachnaya, V. O. [1 ,2 ]
Lutsiv, V. R. [1 ]
Malashin, R. O. [1 ,2 ]
机构
[1] St Petersburg State Univ Aerosp Instrumentat, Bolshaya Morskaya 67, St Petersburg 190000, Russia
[2] Russian Acad Sci, Pavlov Inst Physiol, Naberezhnaya Makarova 6, St Petersburg 199034, Russia
关键词
visual speech recognition; sign language recognition; affective computing; comput-er vision; neural networks; SIGN-LANGUAGE; EMOTIONS; DATABASE;
D O I
10.18287/2412-6179-CO-1154
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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 compo-nents, conveying the informational part of a message and its emotional part respectively. A com-plex 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 inher-ent 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 para-verbal and non-verbal components of communication. Challenges of designing such databases and systems are specified. Prospective directions in complex analysis of all communication compo-nents and its combinations for the most complete evaluation of messages are defined.
引用
收藏
页码:287 / +
页数:20
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