Brands that Trust LexiConn for Content Tagging
Why LexiConn for Video Descriptors
LexiConn brings close to one decade of experience in developing METAdata for 1.4 Lakh+ episodes of multilingual episodes.
We have the process maturity to design systems, processes and workflows to handle over 2500 hours of content each month.
Our extensive reach and a network of freelance writers allows us to process multi-language shows with considerable ease.
Our team pays meticulous attention to detail, ensuring that the metadata is accurate and aligned with the story's narrative.
Whether you require blog posts, social media updates, copy for banners or newsletters, we have the tools, skill, and know-how.
We handle large-scale, real-time content requirements across time zones and formats to ensure that your fans never miss an update.
These models include Classification Models (to classify videos as "comedy," "action," "drama," etc.) and Tagging Models(to automatically describe objects, scenes, or actions in the video.)
Common NLP techniques used for video content analysis are Tokenization, Named Entity Recognition (NER), and Sentiment Analysis.
Some common computer vision techniques used for video descriptor extraction are Color Histograms, Texture Descriptors, and Motion Vectors. CV algorithms extract visual features, useful for descriptors for content discovery and recommendation.
Some of the features offered by these APIs include Object Recognition, Scene Detection, Sentiment Analysis, and Keyframe Extraction. APIs help developers leverage sophisticated video analysis tools without having to implement them from scratch.
Some widely used libraries include OpenCV (Open Source Computer Vision Library) and NLTK (Natural Language Toolkit). Developers utilize these libraries and customize their video descriptor extraction workflows.
Looking to Outsource Video Descriptors?
Experience quality and reliability at scale. Talk to LexiConn for a team that can deliver high-quality video descriptors for multiple languages.Discuss a Pilot
Popular Video Descriptors
Each update begins with the episode number and the date it aired, and the episode title (if any).
To categorize content, facilitate organization, filtering, and recommendation based on preferences.
Helps in recommending videos that align with a user's viewing preferences and time availability.
For catering to users who prefer videos in specific languages or require subtitles for accessibility reasons.
Aids in content cataloging and enables platforms to recommend videos with specific visual content.
Textual representations of video content, making it searchable and accessible and helping content discovery.
Get Metadata and Video Descriptors
If you are a video content creator, a TV channel, or a streaming company we know the challenges you face in getting your content discovered. Catching the audience's attention and gaining traction can be quite the uphill battle.
This is where we come in. LexiConn's has helped India's leading OTT platform develop metadata for over 65000 episodes, reduce their time to market, and achieve exponential growth.
So, if you're looking to give your content the spotlight it deserves, LexiConn has the answer.