VTT to TXT — Extract Text from WebVTT Captions
Use this free VTT to TXT converter to pull clean, readable text out of WebVTT caption files. The tool strips the WEBVTT header, timestamps, cue settings, voice tags, and formatting markup so you get a plain text output ready for translation, review, text analysis, or study material creation.
Drag & drop your file here
or click to browse · Accepts .vtt files
Don't lose the subtitle structure
Need timed subtitles instead of plain text? Convert VTT to SRT. Need to rebuild subtitles from this text later? Use TXT to SRT.
How to Extract Text from VTT in 3 Steps
- 1
Upload your VTT caption file
Drop a .vtt file from any source — course platforms, YouTube, streaming services, or browser-based video tools.
- 2
Strip all caption metadata
The converter removes the WEBVTT header, timestamps, cue settings, voice tags, and formatting to isolate the spoken text.
- 3
Download the plain text transcript
Save the .txt file for translation, review, text analysis, or any workflow where you need the spoken content without subtitle syntax.
What Gets Removed During VTT to TXT Extraction
- WEBVTT header:The required header line and any metadata fields (Kind, Language) that follow it are removed entirely.
- Timestamp lines:All timing information including start time, end time, and the arrow separator are stripped. The text output has no timing references.
- Cue settings:WebVTT cue settings like position, size, alignment, and line placement are removed because plain text has no layout model.
- Voice and class tags:Tags like <v Speaker> for voice identification and <c.classname> for CSS styling are stripped. Only the visible spoken text remains.
- NOTE blocks:WebVTT comment blocks (NOTE followed by text) are editorial metadata and are removed from the text output.
Common Use Cases for VTT to TXT
- Creating transcripts from course captions:Online learning platforms (Coursera, Udemy, edX) often provide captions as VTT files. Extracting the text gives students a study document they can annotate, search, and review offline.
- Preparing text for translation:Translators work with clean text, not subtitle syntax. Extracting dialogue from VTT produces a document that can go directly into translation tools or CAT software.
- Running text analysis or NLP processing:Researchers and content teams sometimes need to analyze the spoken content of videos. Stripping VTT to plain text removes the structural noise that would interfere with word frequency analysis, sentiment analysis, or keyword extraction.
- Building accessible content archives:Plain text transcripts are the most accessible format for screen readers, search indexing, and long-term archiving. Converting VTT to TXT creates a permanent text record of the spoken content.