Sports broadcasters manage high volumes of video footage daily. Our team developed an AI-driven Automated Title Generation Engine that converts raw sports footage into compelling, engagement-focused video titles—instantly and consistently.
Problem Statement
Manual creation of titles for sports clips was slow, subjective, and impossible to scale. Editors often missed emotional game moments, resulting in generic titles that performed poorly and failed to maximize reach or viewer engagement.
Affected Areas
Inefficient use of editing manpower
Inconsistent title quality across videos
Low click-through rates due to generic, non-emotive titles
Inability to scale content output during high-volume seasons
Solution
We built an intelligent title generation workflow combining speech analysis, entity extraction, emotion/context interpretation, and GenAI summarization to deliver human-quality titles at scale.
How We Implemented
Video Ingestion:
via AWS Media Services
Speech-to-Text Processing:
with Whisper
Keyword Extraction & Named Entity Recognition:
using NLP models (BERT)
Abstractive Summarization:
with GenAI to craft emotionally resonant titles
Automated Deployment & Integration:
through GitHub Actions
Outcome
Our AI-powered system delivers an 80–90% reduction in editorial workload, allowing teams to focus on strategic initiatives rather than repetitive tasks. By generating contextual and emotionally engaging titles, it drives higher viewer engagement and keeps audiences hooked. The platform is fully scalable, capable of processing thousands of videos seamlessly, while maintaining a consistent brand voice across all generated content. This ensures efficiency, quality, and audience connection at every step.
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