ListLang – Learn Languages to Fluency

Hacker News

Depending on the language, the top 1,000 most frequently used words account for ~85% of all speech and text, and the top 5,000 account for ~95%. It’s really important to learn these words. Learning words in context helps you naturally understand their meaning and use cases, while avoiding the rote memorization of definitions. ListLang helps you achieve fluency by learning the 5,000 most frequently used words in context. Most language learning apps never move past beginner level content. This method requires some basic knowledge, but otherwise it should rapidly increase your level past the intermediate level and into the advanced level. I built this app because I studied Spanish and Russian for many years in school, but when I traveled to Argentina and Russia, I realized I didn’t know enough vocabulary to meaningfully communicate with the people there. I hope it will be helpful for you.

Visit product View on Hacker NewsFeb 8, 2023

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

82%82% 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.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

65%65% 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 · Strong signals: apps · Missing: mobile apps, ios, personal

54%54% 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

25%25% 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

22%22% 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.

Correct prediction on native model

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