Convert audio or video files to text

Hacker News

Hey HN, we created a free audio/video transcription and editor that you can use for free. You can detect cheers, applause, filler words, edit transcript to edit audio, create audiograms and export in different formats. We also have a chrome extension that transcribes any audio/video on the page you are on. After transcription you can follow along with the audio and read the transcribed text while the audio is playing. You can search for spoken content in a podcast or other audio/video content in your browser. There are some limitations, our product only works on Chrome and Firefox, we only support english for now and audio longer than an hour is not guaranteed to be transcribed (we will lift this limitation soon) links: https://revoldiv.com chrome extension: https://chrome.google.com/webstore/detail/revoldiv/cjjljbmei...

Visit product View on Hacker NewsJan 28, 2022

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

75%75% 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: google · Missing: mac, agents, macos

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

47%47% predicted probability of success on AppSumo, 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

26%26% 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 · 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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