Phrasing – learn every language, to any level

Hacker News

Hey there HN - Today I'm sharing a demo of my our language learning tool, Phrasing. It's a tool born from the language acquisition hypothesis, too many hours in an anki slog, and a strange desire to always be learning obscure languages. The method is simple: 1. type in a show 2. learn the most important words 3. watch the show/acquire the words 4. review the words when needed in the future. On top of that, we're trying to: - do some novel things with spaced repetition (no more anki slog) - expand the sort of content you can learn from (I want to to refresh my French by reading The Stormlight Archive) - make an insanely beautiful tool for all languages (I want to learn Sanskrit and Hawaiian and such) I think we're off to a great start so far, and I'm happy to be able to share what we have already! We've taken some of our core features, and ripped them out to put them on a playground for HN to explore. There's so much more to come though, this is just the beginning. I'll be here all day to answer any questions. Thanks for checking it out and have a wonderful day <3 EDIT: This link was meant as a demo so hacker news has something to click around on (as per the rules of Show HN). The main marketing page can be found at https://phrasing.app/ - I think that's causing some confusion

Visit product View on Hacker NewsJan 29, 2024

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

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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