CleanerAudio – AI to clean and transcribe audio

Hacker News

Hi HN, I was making family vlogs but the audio was ruined by wind noise. Existing tools felt clunky or expensive, so I built my own. https://cleaneraudio.com/ CleanerAudio lets you: • Clean noisy recordings • Transcribe audio or YouTube videos • Summarize long videos • Download YouTube audio as MP3 Built with React (Vite), Prisma, Postgres, and AI models for noise reduction, transcription, and summarization. There’s a free tier — I’d love your feedback on what works and what doesn’t.

Visit product View on Hacker NewsAug 29, 2025

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Launch Intel predictions

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

67%67% 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.

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

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, models, recordings · Missing: mac, agents, macos

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

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

35%35% 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

29%29% 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

20%20% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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