Моделирование базового переводчика индонезийского языка жестов на одноплатном компьютере Raspberry Pi

Глухие люди имеют потерю слуха от легкой формы до очень тяжелой. Такие люди испытывают трудности при обработке языковой информации, как со слуховыми аппаратами, так и без них. Глухие люди, которые не применяют слуховые аппараты, в своих повседневных разговорах используют язык жестов. В то же время здоровым людям трудно общаться с глухими, поэтому для общения они должны знать язык жестов. В Индонезии существует два жестовых языка, а именно Indonesian Sign Language System (SIBI) и Indonesian Sign Language (BISINDO). Разработана модель для помощи в общении между глухими и здоровыми людьми. Модель рассмотрена на примере использования одноручного метода SIBI и доработана с использованием одноручного и двуручного BISINDO. Основная функция метода — распознавание основных букв, слов, предложений и цифр с помощью одноплатного компьютера Raspberry Pi и камеры, которые предназначены для обнаружения движений языковых жестов. Полученные изображения переводятся в текст на экране монитора с помощью специальной программы. Используемый метод заключается в обработке изображений и машинном обучении с использованием языка программирования Python и техники сверточной нейронной сети. Прототип устройства выдает предупреждение о необходимости повторить язык жестов, если перевод не удался, и удалить перевод, если он не соответствует базе данных. Прототип устройства требует дополнительных исследований для обеспечения гибкости при считывании динамических движений, выражений лиц, и перевода слов, не включенных в существующую базу данных. Также требуется расширение базы данных, отличной от языка жестов SIBI, например, BISINDO, или языков жестов из других регионов или стран.

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