Turn documents into lip-synced video readers

Hacker News

I read a lot of pdfs and papers, and I bounce between "read it myself" and "listen to it". So for quite some time wanted to experiment with adding a lip-sync video. I wanted something that keeps the original page in front, narrates it and show exactly where word-by-word with the lip-sync video reading it - Closer to a YouTube explainer than an audiobook. I’d be interested in feedback on the interaction model, the usefulness of lip-synced presenters for reading, and where this kind of tool would be most valuable: education, accessibility, research, documentation, or something else.

Visit product View on Hacker NewsJun 29, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, plain · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: video, education · Missing: mobile apps, ios, personal

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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