Me

Melo Rhythm – A Piano Teacher's Take on Music Dictation App

Hacker News

Melo Rhythm – A Piano Teacher's Take on Music Dictation App

Hello Hacker News community! I'm excited to showcase my latest project, Melo Rhythm. Melo Rhythm is a unique blend of my musical expertise and my passion for coding. It's built primarily in JavaScript (abcjs, tonaljs, threejs, react), wrapped in React Native for a seamless mobile experience, and uses Keycloak for secure Single Sign-On functionality. The backend is a straightforward ExpressJS setup, focusing on efficiency and scalability, primarily used only for storing and syncing progress. The app is offline-first, meaning that, for example, on mobile, once you log in, you can use it in flight mode, but once online, it syncs your progress across devices. For monetization, I'm using subscriptions, and the App is already available on Google Play. If the Android version of the mobile part of the app gains some traction, I'll release it for the App Store as well. I was motivated by the fact that I could not find a music dictation app that would combine rhythm and melody dictation into melo-rhythmic dictation, which is very important for musicians. I paid much attention to music entry optimization, so that should be the biggest advantage (apart from there being, as far as I can tell, no rhythm+melody dictation apps on mobile stores). Other than that, I spent a lot of time creating and thinking about curricula; for example, the Pro curriculum has around 90 levels. If there is interest, I might create a blog post to delve deeper into the features and technical aspects. Check out the web version of Melo Rhythm here: https://k3y.me Download Melo Rhythm on Google Play : https://play.google.com/store/apps/details?id=com.antiropy.melorhythm I would be grateful for feedback, suggestions, and discussions from both the Hacker News community and music enthusiasts. Your insights are vital in refining Melo Rhythm and enhancing its impact.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
97%97% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, new · Missing: mac, agents, macos
70%70% 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
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, hacker news, io · Missing: https docs, just released, exist
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: apps, google · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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