Real-Time Debate Annotation App
Budget: $250 – $750 USD
I’m building a small app that listens to a two-person debate in real time, turns everything they say into text, and layers on rich, automatic annotation so the final transcript does more than simply record words.
Core flow
• The tool records live audio from both speakers (simultaneous mic capture is fine).
• Speech is transcribed on the fly with accurate speaker diarisation.
• Natural-language processing tags each utterance: questions, answers, follow-ups, objections, digs, attempts at humour or sarcasm, etc.
• Visually, the transcript is formatted right away—colour codes for tone, italics for emphasis, bold for critical points—so both sides can see at a glance what mattered.
• At the end a summary block shows which questions were answered, which objections were ignored, and where speakers talked past each other.
Key expectations
1. One-click start/stop recording and automatic transcript generation.
2. Objective tagging logic that can be tweaked with simple rules or a model update.
3. Export to PDF, DOCX, and Markdown while preserving colours and styling.
4. Clean, browser-based interface is preferred, but I’m open to desktop if it speeds delivery.
5. Code should be commented and ready for hand-off; Python or JS stacks are both acceptable, and leveraging existing speech-to-text engines (e.g. Whisper, Google Speech API) is encouraged.
Acceptance criteria
• A five-minute live test debate produces an annotated transcript with >90 % word accuracy, correct speaker labels, and visible tags for every direct question/answer pair.
• The visual summary correctly counts answered vs. unanswered questions.
• Export files match the on-screen formatting.
Please outline the approach you’d use, any libraries or APIs you’d recommend, and an estimated timeline for a working prototype.
Core flow
• The tool records live audio from both speakers (simultaneous mic capture is fine).
• Speech is transcribed on the fly with accurate speaker diarisation.
• Natural-language processing tags each utterance: questions, answers, follow-ups, objections, digs, attempts at humour or sarcasm, etc.
• Visually, the transcript is formatted right away—colour codes for tone, italics for emphasis, bold for critical points—so both sides can see at a glance what mattered.
• At the end a summary block shows which questions were answered, which objections were ignored, and where speakers talked past each other.
Key expectations
1. One-click start/stop recording and automatic transcript generation.
2. Objective tagging logic that can be tweaked with simple rules or a model update.
3. Export to PDF, DOCX, and Markdown while preserving colours and styling.
4. Clean, browser-based interface is preferred, but I’m open to desktop if it speeds delivery.
5. Code should be commented and ready for hand-off; Python or JS stacks are both acceptable, and leveraging existing speech-to-text engines (e.g. Whisper, Google Speech API) is encouraged.
Acceptance criteria
• A five-minute live test debate produces an annotated transcript with >90 % word accuracy, correct speaker labels, and visible tags for every direct question/answer pair.
• The visual summary correctly counts answered vs. unanswered questions.
• Export files match the on-screen formatting.
Please outline the approach you’d use, any libraries or APIs you’d recommend, and an estimated timeline for a working prototype.