The document explains that Quantiphi’s AI-powered closed captioning engine helps broadcasters and OTT platforms scale captioning while meeting FCC accessibility standards. It addresses challenges such as long manual turnaround times, high skill requirements, variable costs, and weaknesses in standard speech-to-text models, including high word error rates, poor jargon handling, and difficulty with speaker changes and background noise. Page 2 shows an active-learning pipeline combining speech-to-text, NLP, and human review to produce accurate, synchronized captions. Features include diarization, auto-punctuation, and multilingual support. A case study shows 85%+ accuracy and real-time captions for a major US news broadcaster.

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