Анализ мультимодальных данных в распознавании эмоций
https://doi.org/10.18255/1818-1015-2025-3-252-281
Аннотация
Использование мультимодальных данных в системах распознавания эмоций имеет огромный потенциал для приложений в различных областях: здравоохранение, человеко-машинные интерфейсы, контроль состояния операторов, маркетинг. До недавнего времени развитие систем распознавания эмоций на основе мультимодальных данных сдерживалось недостаточной мощностью вычислительной техники. Однако с появлением высокопроизводительных систем на основе графических процессоров и разработкой эффективных архитектур глубоких нейронных сетей произошел всплеск исследований, направленных на использование нескольких модальностей, таких как аудио, видео и физиологические сигналы, для точного определения человеческих эмоций. Помимо этого, немаловажную роль стали играть физиологические данные, полученные с помощью носимых устройств, благодаря относительной простоте их сбора и точности, которую они позволяют достигать. В данной статье рассмотрены архитектуры и методы применения глубоких нейронных сетей для анализа мультимодальных данных с целью повышения точности и надежности систем распознавания эмоций, представлены современные подходы к реализации таких алгоритмов и существующие открытые наборы мультимодальных данных.
Об авторах
Даниил Алексеевич Бердышев
Московский государственный университет им. М.В. Ломоносова
Россия
Россия
Алексей Геннадиевич Шишкин
Московский государственный университет им. М.В. Ломоносова
Россия
Россия
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Рецензия
Для цитирования:
Бердышев Д.А., Шишкин А.Г. Анализ мультимодальных данных в распознавании эмоций. Моделирование и анализ информационных систем. 2025;32(3):252-281. https://doi.org/10.18255/1818-1015-2025-3-252-281
For citation:
Berdyshev D.A., Shishkin A.G. Multimodal data analysis in emotion recognition: a review. Modeling and Analysis of Information Systems. 2025;32(3):252-281. (In Russ.) https://doi.org/10.18255/1818-1015-2025-3-252-281
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