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I built a language practice app with GPT-3

Hacker News

I built a language practice app with GPT-3

Hey, everyone! I am happy to introduce you to Lingobo – an AI language partner As someone who has studied French for 8 years and can read it fairly well, I still find myself at a loss when it comes to speaking it. My knowledge of French never seemed to translate into a useful active skill and I lacked the confidence to practice it in real-life conversations. This was a paradox I wanted to solve. Utilizing GPT-3, I created a French language partner for myself, allowing me to practice conversational skills without worrying too much about grammar, tenses, and spelling. I have since built it out as a web application named Lingobo and expanded it to include a total of 14 languages: English, French, Spanish, German, Italian, Polish, Portuguese, Japanese, Chinese, Korean, Russian, Indonesian, Hindi, and Dutch. Hope you like it and find it useful! Any feedback is welcome

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting
71%71% 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.
TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
53%53% 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
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Strong signals: introduce · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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