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Translate foreign words and learn them as flashcards

Hacker News

Translate foreign words and learn them as flashcards

I created this browser extension and mobile app to look up unfamiliar foreign words and learn them as flashcards on my mobile device. There are multiple solutions to do that, but my itch was that all the solutions make it difficult to create a high-quality flashcard: - nouns have to be saved as singulars - verbs have to be saved as infinitives - each word has to have a description Works well (at least for the Dutch language). I have created around 900 cards, primarily good out of the box. What do you guys think about it?

Visit product View on Hacker NewsFeb 8, 2024

Actual performance

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

46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

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

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

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting

35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

34%34% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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