Voice Overlay for iOS and Android Apps

Hacker News

We're seeing at Algolia a lot of developers implementing speech to text in their mobile apps, but didn't see much in the way of tooling to help them do it. So we set out to fix it, and wanted to release it not just for our users, but for any devs who want to do this. iOS/Swift: https://github.com/algolia/voice-overlay-ios/ Android/Kotlin: https://github.com/algolia/voice-overlay-android/ We wanted to take away the boilerplate necessary and leave the UI and other customizations in place. We've been looking forward to sharing this with the HN community and getting your feedback!

Visit product View on Hacker NewsOct 2, 2018

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

85%85% 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 · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

73%73% 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

49%49% 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 · Strong signals: users · Missing: plus, platform, intuitive

33%33% 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

28%28% 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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