AutoPTT – Voice-activated push-to-talk

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Hello HN. I made this Windows desktop app that allows using voice activation with games or apps that only support push-to-talk. The initial version was written years ago, without any UI or configuration options. It was just for my personal use. I had told a few friends about it, though, and then one of them asked if he could get a copy to use with Discord priority speaker, since for years, it has only worked with push-to-talk. So I spent some time making a more user-friendly version. It's written almost exclusively in C and uses Nuklear [1] for the UI. It has an auto updater. The releases are hashed with BLAKE3 and signed with ECC. I also recently made an open source USB device [2] that the app can use to send input from a "real" keyboard because, it turns out, there are some games (CSGO) that ignore simulated input for activating the microphone. I'm having some trouble finding users though. I've tried posting on a few Discord servers and subreddits for games whose players I suspect would find the app useful but self-promotion and advertising are generally not allowed in these communities, so my posts get removed quite quickly. Any tips on how to best reach my audience? [1] https://github.com/Immediate-Mode-UI/Nuklear [2] https://github.com/veyh/AutoPTT-Sidekick

Visit product View on Hacker NewsAug 23, 2022

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

82%82% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: exclusive, friendly, users · Missing: plus, platform, intuitive

51%51% 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

11%11% 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.

Incorrect prediction on native model

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