Уровень 0 · материалов: 3
В кластер входят документы, описывающие применение Яндексом технологий машинного обучения для обработки текста, речи или картографических данных.
Общие признаки: продукты Яндекса, автоматическая транскрипция, машинное обучение, лингвистическая обработка данных
Группа выше: Технологии и инженерия Яндекса
Смысл: The text explains the technical and linguistic process Yandex used to create a comprehensive Russian-language world map, focusing on the transition from data procurement to the creation of automated transcription systems for 37 languages.
Yandex developed a custom automated transcription system to translate millions of global place names into Russian for its updated World Map service.
Смысл: The text presents the release of a multi-language TTS system designed for the linguistic diversity of Russia and the CIS, highlighting the technical transition to high-quality recording and the implementation of language-specific phonetic and stress-marking logic to achieve natural-sounding speech across 20 different languages.
Silero has released an optimized, high-quality TTS system supporting 20 languages of Russia and the CIS with 95 voices, offering both MIT and CC-NC-BY licensed models.
Смысл: The main idea is that Yandex has successfully applied advanced machine learning and OCR technologies to transcribe complex, handwritten historical Russian archives, transforming a slow manual process of genealogical research into an efficient digital search experience.
Yandex developed a specialized neural network system to automatically transcribe and index handwritten historical archives, significantly accelerating genealogical research.