What this youtube to transcript page is for
Paste a YouTube URL and convert spoken audio to readable text you can publish, quote, search, or feed to AI in 60 seconds.
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YouTube to Transcript
Paste a YouTube URL and convert spoken audio to readable text you can publish, quote, search, or feed to AI in 60 seconds.
Use TranscriptX inside your AI
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Language
Model
Supported Platforms
1000+
Any public video URL
Engine
AI
Accuracy
99.2%
YouTube
TikTok
Instagram
X
Facebook
LinkedIn
Reddit
Vimeo
Twitch
Rumble
Threads
SoundCloud
Bilibili
Snapchat
1000+ more
YouTube
TikTok
Instagram
X
Facebook
LinkedIn
Reddit
1000+ more
Transcription Engine
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READY
Why teams use TranscriptX for YouTube
Use one URL-to-text workflow to extract accurate transcripts, preserve timestamps, and repurpose spoken content into publish-ready assets.
FAQ
How accurate is conversion?
About 95% on clear audio, 88-92% on noisy real-world recordings. Higher than YouTube's native auto-captions across every content type we've tested. Full numbers in our <a href="/research/transcription-accuracy-benchmark">benchmark</a>.
Can I process long videos?
Yes. Practically no upper limit. A 1-hour video processes in 60-90 seconds; a 4-hour podcast in 3-5 minutes. The model handles long-form fine.
What languages are supported?
90+ with automatic detection. English, Spanish, French, German, Portuguese, Italian, Japanese, Korean, Mandarin, Arabic, Russian, Turkish, Hindi, Vietnamese, Thai — all the major languages with substantial training data.
Does it work on YouTube Shorts?
Yes, paste the Shorts URL like any video.
Is my video data used for AI training?
No. We don't use your content to train models. Transcripts are stored only so you can re-download them.
Can I convert from a YouTube playlist URL?
Currently you paste each video URL individually. Playlist-batch is on the roadmap. For now, our manual batch input handles up to 10 URLs at once on paid tiers.
Does the conversion include speaker labels?
No, we don't add named speaker labels. Otter handles speaker diarization better for multi-person recordings.
Can I use this for offline analysis?
Yes — export as JSON or TXT, then use offline. The transcript file is yours to keep, search, or feed into other tools.