My new tool enhances sound design with video-based audio generation

Hacker News

Hello HN! We've built an AI-powered sound design tool that makes professional audio more accessible. While immersive audio is key for engaging videos, the process is often overlooked because it is time-consuming and technically challenging. Our key features are: Video analysis for tailored sound effect & ambience suggestions Instant AI-generated audio based on our recommendations or a user description We're still in active development, so we'd really appreciate any feedback or critiques on our approach and implementation. We can't wait to hear your thoughts! Chris, Ben & Alex Demo: https://youtu.be/_xgZeJlL3RY App: https://app.adorno.ai/

Visit product View on Hacker NewsApr 10, 2024

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

82%82% 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.

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

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

12%12% 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

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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