AI Live Cricket Commentator

I already have raw ball-by-ball cricket data streaming into an event detector and now I want to turn it into a YouTube-ready broadcast with natural-sounding, monetisable voice-over. Your first mission is to wire the whole chain directly to YouTube Live so the feed appears in real time with no manual intervention. Once that backbone is solid, we will refine the AI commentary generator so the output feels like a seasoned color commentator: pointing out relevant player statistics, quick tactical analysis and the occasional historical nugget that keeps viewers hooked.

The workflow I envision is straightforward:

• Live cricket data → event detector (already working)
• Your code – commentary module + TTS – stitches in real-time
• RTMP push to YouTube Live with dynamic scoreboard overlay

Key points you’ll tackle
– Build or adapt an RTMP/FFmpeg pipeline that streams both video and the AI-generated audio directly into my channel’s live event dashboard.
– Design or fine-tune the NLP model so it produces purely color commentary; play-by-play is handled elsewhere. The text must reference player stats, game situations and cricket heritage whenever context permits.
– Feed that text into a neural TTS that resembles a professional broadcaster’s tone yet remains unique enough for YouTube to recognise as original, ensuring channel monetisation.
– Keep latency under five seconds from data event to spoken line so viewers feel it is truly live.

Deliverables
1. End-to-end script(s) or containerised setup (Python preferred) that ingests the existing JSON data feed, produces commentary, synthesises speech and streams to YouTube Live.
2. Model artefacts and configuration files for the commentary generator and the voice model.
3. A short recorded demo plus setup notes so I can replicate the stream on my machine.
4. Final hand-off session walking through deployment and answering any integration questions.

Acceptance criteria
• The live stream starts with a single command and shows synced video, scoreboard and AI voice within YouTube Studio.
• Commentary accuracy: at least 90 % of generated lines correctly reference current players or match context.
• Voice quality is human-like with no policy strikes during a 30-minute test run.

If you’ve previously worked with NLP for sports, Transformer-based text generation, Tacotron, FastSpeech, or real-time RTMP pipelines, you’ll feel right at home. Let’s bring cutting-edge AI banter to cricket fans worldwide.