Lecture Transcript Scraper (YouTube)

Turn YouTube lectures and full courses into clean transcripts — paste a course playlist, a university channel or single lecture URLs and get plain text, SRT and VTT for every lecture in one run. Built for students, researchers and note-taking workflows.

⚡ Quick start (10 seconds): paste one YouTube link below, press Start, and download your files from the Storage → Key-value / Dataset tab when the run finishes — TXT transcript plus SRT/VTT subtitle files for every video.

Example output per video
├─ transcript.txt   "Welcome back everyone, today we..."
├─ subtitles.srt    1
00:00:01,000 --> 00:00:03,200
Welcome back...
└─ subtitles.vtt    WEBVTT ...

Typical searches this Actor answers: youtube transcript scraper, youtube transcript api, youtube to srt api, download youtube subtitles as srt, youtube captions to text, youtube transcript api, extract closed captions, bulk youtube subtitle download.

What you get per video

• srt — ready-to-save SubRip file content
• vtt — ready-to-save WebVTT file content
• transcript — clean plain text
• segments — [{start, duration, text}] for precise timing work
• language, languageName, isAutoGenerated, availableLanguages
• Video metadata: title, channel, duration, views, publish date

Bulk input: playlists & whole channels

Paste a playlist URL (expands to up to ~100 videos) or a channel URL / @handle (latest 15 videos) alongside normal video URLs — everything is expanded automatically and transcribed in one run. maxVideosPerSource caps the expansion.

Use cases

• Turn recorded university lectures into readable notes
• Make course content searchable and quotable for research
• Prepare accessible text versions of teaching material

Input

Paste video URLs (or IDs), pick preferred languages (fallback is automatic), toggle timestamps/SRT/metadata. Batches run concurrently.

Pricing

Pay per result: you are charged only for videos that actually return subtitles. No subscription, no monthly fee.

Why teams use it

Subtitle files for video localization and accessibility, transcripts for LLM/RAG pipelines, caption corpora for research, and content repurposing at scale — without browser automation or API keys.