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Современные технологии автоматического распознавания средств общения на основе визуальных данных
В.О. Ячная 1,2, В.Р. Луцив 1, Р.О. Малашин 1,2

1 Государственный университет аэрокосмического приборостроения,
190000, Россия, г. Санкт-Петербург, ул. Большая Морская, д. 67 лит. а;
2 Институт физиологии имени И.П. Павлова РАН,
199034, Россия, Санкт-Петербург, наб. Макарова, д. 6

 PDF, 1106 kB

DOI: 10.18287/2412-6179-CO-1154

Страницы: 287-305.

Аннотация:
Общение представляет собой широкий спектр различных действий, связанных с приёмом и передачей информации. Процесс общения складывается из вербальных, паравербальных и невербальных компонентов, содержащих информационную часть передаваемого сообщения и его эмоциональную окраску соответственно. Комплексный анализ всех компонентов общения позволяет оценить не только содержательную составляющую, но и ситуативный контекст сказанного, а также выявлять дополнительные факторы, относящиеся к психическому и соматическому состоянию говорящего. Существует несколько методов передачи вербального сообщения, среди которых устная и жестовая речь. Речевые и околоречевые компоненты общения могут содержаться в различных каналах данных, таких как аудио- или видеоканалы. В данном обзоре рассматриваются системы анализа видеоданных ввиду того, что аудиоканал не способен передать ряд околоречевых компонентов общения, вносящих в передаваемое сообщение дополнительную информацию. Проводится анализ существующих баз данных статических и динамических образов и систем, разрабатываемых для распознавания вербальной составляющей в устной и жестовой речи, а также систем, оценивающих паравербальные и невербальные компоненты общения. Обозначены сложности, с которыми сталкиваются разработчики подобных баз данных и систем. Также сформулированы перспективные направления разработок, связанные в том числе с комплексным анализом всех компонентов общения с целью наиболее полной оценки передаваемого сообщения.

Ключевые слова:
распознавание речи, распознавание жестовых языков, аффективные вычисления, компьютерное зрение, нейронные сети.

Благодарности
Работа выполнена при поддержке Госпрограммы 47 ГП «Научно-технологическое развитие Российской Федерации» (2019-2030), тема 0134-2019-0006.

Цитирование:
Ячная, В.О. Современные технологии автоматического распознавания средств общения на основе визуальных данных / В.О. Ячная, В.Р. Луцив, Р.О. Малашин // Компьютерная оптика. – 2023. – Т. 47, № 2. – С. 287-305. – DOI: 10.18287/2412-6179-CO-1154.

Citation:
Yachnaya VO, Lutsiv VR, Malashin RO. Modern automatic recognition technologies for visual communication tools. Computer Optics 2023; 47(2): 287-305. DOI: 10.18287/2412-6179-CO-1154.

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