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Chessophone – Generate music from chess games

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Chessophone – Generate music from chess games

Chessophone takes a PGN string representation of a chess game and generates music - Notes from the C major scale are added for each piece in each row of the board for each move in the game. Games played with the same opening will sound the same until they deviate from book moves. The perceived tempo of the music speeds up as pieces are captured. Enjoy! Created with python-chess and tone.js. Source code here: https://github.com/charliemeyer/chessophone

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
66%66% 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 · Missing: mobile apps, ios, personal
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: notes, code, open · Missing: mac, agents, macos
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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