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Perfect Pitch Puzzle – a musical Wordle daily ear training game

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Perfect Pitch Puzzle – a musical Wordle daily ear training game

Hi all! Thanks for checking out the side project my family and I have been working on (on and off) for the past year. We were playing wordle when we thought: wouldn't it be fun if you had to guess musical notes (ABCDEFG) instead of words? And what if the notes you had to guess were actually the first six notes of a familiar melody? My brother and I both have perfect pitch, which has been really helpful when we want to cover a song that we like, or improvise in a jazz or blue grass setting. We don’t promise that this game will help you gain perfect pitch, but it is possible to train your ear to more accurately gauge sounds, and our hope is that this game will help with that. So far we’ve gotten feedback from consistent players that the game has helped non-musicians more easily identify notes based on relative pitches, and helped even musicians improve their ability to remember tunes better, which is good to hear. The game has evolved with different instruments and difficulty modes (easy, normal, hard), but the essence has remained the same: - One new musical puzzle a day - The octave moves with the melody, so you don’t need to worry about the octave; you just need to guess the pitch There are a few things we want to improve as well, like: - improved mobile support (especially Android) - a “practice mode” - allow users to play more than one game per day, or multiple variations of notes, with visual feedback on how close they were to guessing the note - making it easier to add new songs to the database (currently it takes 5-10 minutes to code in a new song) any other feedback that we get here or in our Discord. :) PS. If you already have perfect pitch or want to challenge yourself to the impossible, I'd recommend playing the "bird_tweet" instrument in "hard" mode!

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Indie HackersFits the IH revenue-focused audience · Strong signals: songs · Missing: supports, reddit linkedin, podcasting
93%93% 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: user, new, visual · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
20%20% 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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