Lunar Languages – an offline travel phrasebook

Hacker News

So this is a little app I built over Christmas, the idea is to help you very quickly put together key words and phrases when on holiday, just by tapping your way through a menu (no typing), and then be able to see a phonetic translation and also listen to an audio of the phrase I've tried to make it "smart", for example "Can I use" -> "Charger" will give you a translation for "Can I use the charger?" which makes sense in that language, it doesn't just dumbly glue words together This app is - Completely free - Has no ads - Works entirely offline - Contains no analytics or tracking - Collects no data - Has no authentication It's a passion project, and I plan to keep adding to it over the coming year, let me know if you have any feedback, cheers :)

Visit product View on Hacker NewsDec 29, 2025

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

80%80% 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

62%62% predicted probability of success on Indie Hackers, 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

46%46% 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: way · Missing: mobile apps, ios, personal

37%37% 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

35%35% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio, smart · 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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