Subcap – Captions for Videos CC

Hacker News

Subcap is the best mobile app to automatically add captions to videos. Your videos will be much more valuable than ever. Connect with your viewers instantly to make more connections, increase engagement rates, and gain followers, all with an improved video experience. Don't waste time adding subtitles manually. Easily and automatically add captions to your videos, not only in English but also in 125 languages and variants. FEATURES: ~ Record and caption videos instantly with your iPhone or iPad ~ Automatically transcribe videos up to 5 minutes ~ Change subtitles position, size, color, and style, or customize them ~ Use any size video you want ~ Save videos in 1080p or 720p quality with subtitles ~ Download the generated SRT file ~ Add subtitles manually, if needed ~ Share these videos on TikTok, Instagram, Snapchat, IGTV, Facebook, Twitter, Linkedin, Youtube, Youtube Shorts, Instagram Reels for video posts and stories, or via E-Mail, Whatsapp, etc. ~ Use these videos to increase social engagements as perfect content creators and influencers! DEVELOPERS’ NOTE: We’ve realized that making all videos readable would be great for not only the deaf community but also everyone who uses social media actively. We have discovered the need for such an application that makes auto subtitles easily and quickly and supports many languages. With all these thoughts and dreams, we have created this app. What features would you like us to add to the app? Please give us feedback on the comments For more information, please contact us at mail: hello@subcap.app Thank you for your comments and feedback.

Visit product View on Hacker NewsApr 1, 2022

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3points

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best fitHighest predicted score across all platforms for this description.

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

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AppSumoStrong fit for a featured 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

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

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

22%22% 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

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: chat · Missing: web3, crypto, cryptocurrency

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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