Transpose Spotify audio and isolate vocals/instruments in realtime

Hacker News

Sharing a macOS menu-bar app I made that lets you transpose and separate instrument tracks from Spotify songs in realtime. Uses Rubberband engine pitch shifting with formant preservation to avoid the ogre-like sound of pitching down, and HTDemucs converted to Core ML (NN model) to do live audio separation via sliding audio windows. I think this is the best tool of its kind (lowest latency, highest quality, realtime). It's invaluable for me now with karaoke, practicing singing / piano along with Spotify songs.

Visit product View on Hacker NewsAug 24, 2026

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1points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, model · Missing: agents, agent, cursor

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.

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

56%56% 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: para · Missing: mobile apps, ios, personal

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

Indie HackersIH features products with proven revenue · Strong signals: para, songs · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

21%21% predicted probability of success on BetaList, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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