From Content to Audience: A Multimodal Annotation Framework for Broadcast Television Analytics

1. 1Develop a multimodal annotation framework that combines audiovisual and editorial patterns
2. 2Integrate large language models (MLLMs) to automate semantic annotation of broadcast television content
3. 3Evaluate the effectiveness of MLLMs across different pipeline architectures and input configurations
4. 4Apply the framework to real-world broadcast television data to validate its performance

Data scientists and AI engineers on a team can benefit from this framework to improve broadcast television analytics, and product managers can utilize the insights to inform content creation decisions

💡 Multimodal large language models can be effective for automated semantic annotation of broadcast television content

📺 Automate broadcast TV analytics with multimodal annotation framework using MLLMs!