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A browser-based tone generator built with the Web Audio API

Hacker News

A browser-based tone generator built with the Web Audio API

I built maketonesonline.com — a simple browser-based tone generator to experiment with the Web Audio API. What it does: Generates tones from 20 Hz to 20,000 Hz Supports sine, square, triangle, and sawtooth waveforms Lets you adjust frequency, volume, and left/right stereo pan Includes multi-tone, binaural beat, subwoofer/bass frequency, and sweep tone modes It’s useful for testing speakers, hearing tests, exploring sound design, or just seeing how high a pitch you can still hear. Check it out: https://maketonesonline.com I’d love your thoughts, bug reports, or ideas for improvement!

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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