Realtime visualization of 3D spectrogram with THREEJS shaders

Hacker News

I've been working with 2D spectrograms for a while now while working with Speech recognition. It had always fascinated me how speech and words had such distinct features. Looking at spectrograms is essentially like hearing with your eyes. Over the weekend i built a tool to visualize your own audio into a spectrogram in 3D. I used threeJS with shaders and vanilla JS/Html. Play with it here : https://spectrogram-threejs.vercel.app/ I hope it brings you as much joy as it does for me.

Visit product View on Hacker NewsAug 8, 2022

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

71%71% 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: io · Missing: https docs, excited, just released

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: visualize, way · Missing: mobile apps, ios, personal

41%41% 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

31%31% 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 · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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