Libretto – Simple recording and editing, an alternative to Descript

Hacker News

Hi HN, We’re excited to share Libretto – a web-based recording and editing tool designed for creators, podcasters, and teams working remotely. If you’re familiar with Descript, you’ll find Libretto is similar but with unique features and a focus on simplicity. What makes Libretto unique: Local recording for high-quality audio/video: Libretto records media locally on each participant’s device and uploads it in the background, ensuring pristine quality even under poor network conditions. This works like double-ended recording but entirely within your browser. Powerful yet simple editing tools: Transcript-based editing: Edit audio/video as if you’re editing text. Automatic filler word removal: Get rid of "uhs" and "ums" with one click. Core editing tools like splitting, trimming, and cropping are intuitive for non-professionals. Collaborative and browser-based: No downloads required – everything runs in the browser. Teams can work together, sharing projects and edits in real time. Built with: LiveKit for webRTC infrastructure, Deepgram for transcriptions, Rendley’s video editing SDK and Liveblocks for real time shared state. Libretto is free to try, and we’d love your feedback to make it better. If you’re curious, check it out. Questions, thoughts, or suggestions? We’re here to listen!

Visit product View on Hacker NewsNov 15, 2024

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

94%94% 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

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: intuitive · Missing: plus, platform, reviews

71%71% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

67%67% 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: video · Missing: mobile apps, ios, personal

26%26% 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

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: real time, audio · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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