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Bilinual books – books in two languages for language learners

Hacker News

Bilinual books – books in two languages for language learners

Bilinual helps you improve your language skill by providing books that are annotated with translation hints. Bilinual doesn't translate books, but annotates them with translation and language hints. While you should not rely on the translations as a full text, if you don't know the meaning of a word, the hints hopefully provide you a clue to guess the right translation without checking a dictionary. http://www.bilinual.com + I disabled the online annotation features so that the web site can serve more visitors. Please subscribe to the mailing list if you are interested.

Visit product View on Hacker NewsApr 5, 2019

Actual performance

2points

4comments

Did not reach leaderboard

Launch Intel predictions

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

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

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

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

40%40% 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

18%18% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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