I made an open source and local translation app

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A few years ago, right after high school, I decided to try to make a simultaneous translation app for Android as a side project, it took longer than expected (about 2 years) and I had to make a lot of compromises (I had to use Google's API and therefore make users use a developer key because at the time there were no free solutions for speech recognition and translation that had good quality). At the end of university, I decided to pick it up again and finally, using OpenAi's Whisper for speech recognition and Meta's NLLB for translation (with both running locally on the phone), I managed to make it free and totally open-source (as it was meant to be from the beginning). The app is still in beta, so I would love your feedback.

Visit product View on Hacker NewsJun 18, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, openai · Missing: mac, agents, macos

94%94% 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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% 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

21%21% 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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