ClipCast — AI Clips & Pronunciation Guide

ClipCast helps Nigerian radio hosts, podcasters, and broadcast content creators turn long-form audio into ready-to-post social content, without hours of manual work. The problem: broadcasters record for hours but rarely have time to mine episodes for shareable clips. Generic AI tools also treat Nigerian and African names as an afterthought, mispronouncing them on air and in captions, and default to English-only captioning, leaving Yoruba, Igbo, and Hausa audiences out. How it works: upload an audio file or paste a direct URL. ClipCast transcribes it with Speechmatics, then analyzes the transcript with AI/ML API to generate 3-5 timestamped clip suggestions, each with a caption in English, Yoruba, Igbo, and Hausa. Separately, it builds a pronunciation report: names likely to be mispronounced, with a phonetic guide and an AI-scored mispronunciation confidence, so a host can prep before their next read. Approved clips can be exported as text or SRT, or downloaded as trimmed audio, and organized on an internal content calendar. Built entirely in native.builder, through iterative prompting rather than hand-written code. Every integration is real and working: Speechmatics for transcription, AI/ML API for structured analysis, and Supabase for auth, database, storage, and Edge Functions. Along the way, several silent data-pipeline bugs were caught by reviewing the actual generated source against the original spec, including flagged-name confidence scores and multilingual captions that were being generated correctly but never reaching the UI. Known limitation: the AI's language-origin classification for flagged names is strong on common first names but can default to "English" for internationally famous historical figures, likely because the model associates them with the English-language sources it was trained on rather than the name's actual etymology. This is a prompt-tuning refinement for a future iteration; the core pipeline works correctly end to end.