EmotionPlayer: Cutting-Edge Sentiment and Content Analysis for Media

Problem and implemented solution

With the explosion of media content, manual moderation and sentiment analysis are inefficient and error-prone. EmotionPlayer effectively automates media sentiment recognition and content classification.

Nomination

Artificial Intelligence And Digital Services

Topic

Artificial intelligence

Estimated duration of implementation

12-16 months

Implementation geography

EmotionPlayer can be implemented globally, with no specific regional restrictions, making it suitable for use in any locale where video content analysis is needed.

Description of competitive advantages

EmotionPlayer stands out with its pure C implementation for optimal performance, multithreading support for efficient processing, seamless C# integration, and real-time progress tracking, making it a robust and versatile solution for media sentiment and content analysis.

List of awards and prizes, media articles about the organization/individual or the Practice

RUKAMI Fest, winner - https://www.vesti.ru/nauka/article/2488130; VDNH RUSSIA 2023-2024 Member; Junior ML Contest - 2022 winner; Junior ML Contest - 2023 winner - https://ods.ai/tasks/junior-ml-contest

List of scientific works and IP connected with the Practice

Software № 2023669387 from 14.09.2023, Software № 2023660141 from 18.05.2023

EmotionPlayer: Cutting-Edge Sentiment and Content Analysis for Media

Contacts

Partners