What this audio to transcript page is for
TranscriptX extracts audio from supported video URLs (and audio-only URLs) and converts speech to clean transcript text in under a minute.
System Status: Online
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Audio to Transcript
TranscriptX extracts audio from supported video URLs (and audio-only URLs) and converts speech to clean transcript text in under a minute.
Use TranscriptX inside your AI
Paste a video or audio link to get started.
Drop your recording here
Video or audio from your device
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
Guides →
READY
Why teams use TranscriptX for Audio from video URLs
Use one URL-to-text workflow to extract accurate transcripts, preserve timestamps, and repurpose spoken content into publish-ready assets.
FAQ
Do I need to download MP3 first?
No. TranscriptX handles audio extraction internally from URL input. Paste a YouTube/Vimeo/podcast URL directly — we extract the audio automatically.
Does it support multiple languages?
Yes — 90+ languages with automatic detection. Strongest in English, Spanish, French, German, Portuguese, Italian, Japanese, Korean, Mandarin, and Arabic.
Can I transcribe a podcast episode from Spotify?
Yes for publicly available episodes — paste the Spotify episode URL. Same for Apple Podcasts, SoundCloud, and most RSS-distributed podcasts.
What about voice memos from my phone?
Upload to Google Drive with "Anyone with the link" sharing, then paste the Drive file URL. See our <a href="/help/upload-audio-file-transcript">file upload help page</a> for the exact steps.
What audio file formats work?
Common ones — MP3, M4A, WAV, OGG, AAC, FLAC. If it plays in standard media players, it usually works for us.
How long can the audio be?
Practically no upper limit, though long audio (3+ hours) takes proportionally more processing. We've successfully transcribed 4+ hour podcasts.
Does this work for multi-speaker conversations?
Transcription works fine; we don't separate speakers into named labels though. For multi-person recordings where labels matter, Otter's diarization is better.
Can I get accurate transcripts of music lyrics?
In principle yes, but our engine is tuned for speech, not singing — accuracy on music drops significantly. For lyric transcription, dedicated lyric tools usually do better.