YouTube Transcript Scraper

YouTube Transcript Scraper: captions as text, timed segments, SRT and VTT

Paste watch, Shorts, live, embed or youtu.be links or bare 11 character ids, or just type a search, and each video comes back as one row holding the full plain text, the timed segments, a ready-to-save SRT and a ready-to-save WebVTT. No API key, no cookies, no login.

The honest limit: it reads caption tracks the video already has. It does not listen to the audio, so a video nobody captioned and that YouTube never auto-captioned comes back as NO_TRANSCRIPT, and no setting changes that.

📝 What YouTube Transcript Scraper does

For each video it finds the caption tracks, picks one using languagePreferences in order, and pulls the cues. An exact match wins, then a base-language match, so pt-BR falls back to pt. If none of your preferences exist it takes another available track rather than failing the video, and detectedLanguage tells you what it actually used.

Manual captions are preferred over auto-generated ones when both exist. isAutoGenerated says which you got, and availableLanguages lists everything the video had, so you can re-run for a different one.

Type something into searchKeywords instead and it searches YouTube, takes the top maxVideosPerSearch videos from each search, and handles them like pasted links. Shorts, channels and playlists are left out of the results. Each row it finds carries searchKeyword and searchRank.

One charge covers the whole row: the plain text, the segments, the SRT, the VTT, the language list and the metadata. There is no per-format or per-language extra. A video that turns up in more than one place, links or searches, is processed once.

📥 What you give it

{
  "videoUrls": [
    "https://www.youtube.com/watch?v=M7lc1UVf-VE",
    "https://youtu.be/dQw4w9WgXcQ",
    "aqz-KE-bpKQ"
  ],
  "languagePreferences": ["fr-CA", "fr", "en"]
}

Or search instead of pasting:

{
  "searchKeywords": ["sourdough for beginners", "no knead bread recipe"],
  "maxVideosPerSearch": 10
}

Run it with empty input and you get one labelled sample row, uncharged, so you can see the shape first.

📤 What you get back

A real row from a real run. text, segments, srt and vtt are cut short here, because the full row is about 20 KB of the same transcript in four shapes:

{
  "ok": true,
  "_sample": false,
  "_diagnostic": false,
  "videoId": "M7lc1UVf-VE",
  "url": "https://www.youtube.com/watch?v=M7lc1UVf-VE",
  "title": "YouTube Developers Live: Embedded Web Player Customization",
  "author": "Google for Developers",
  "channelId": "UC_x5XG1OV2P6uZZ5FSM9Ttw",
  "viewCount": 1656845,
  "durationSeconds": 1344,
  "detectedLanguage": "en",
  "requestedLanguage": "en",
  "isAutoGenerated": false,
  "segmentCount": 466,
  "text": "JEFF POSNICK: Hey, everybody. Welcome to this week's show of YouTube Developers Live. ...",
  "segments": [
    { "text": "JEFF POSNICK: Hey, everybody.", "start": 10.349, "duration": 1, "end": 11.349 },
    { "text": "Welcome to this week's show of YouTube Developers Live.", "start": 11.349, "duration": 2.681, "end": 14.03 }
  ],
  "srt": "1\n00:00:10,349 --> 00:00:11,349\nJEFF POSNICK: Hey, everybody. ...",
  "vtt": "WEBVTT\n\n00:00:10.349 --> 00:00:11.349\nJEFF POSNICK: Hey, everybody. ...",
  "availableLanguages": [
    { "languageCode": "en", "languageName": "English", "isAutoGenerated": false },
    { "languageCode": "en", "languageName": "English (auto-generated)", "isAutoGenerated": true }
  ]
}

🧾 Reading the output

Three kinds of row can land in your dataset, and the flags are how you tell them apart.

The Overview table has no _sample column, so the free sample row reads there as a perfectly good transcript. Filter on _sample == false before counting anything.

The error codes are the useful part of a diagnostic row, and each carries a hint:

A batch where every video fails still finishes as a successful run, with diagnostics and nothing else. Count ok: true rows rather than trusting the run status.

▶️ How to run it

1. Open YouTube Transcript Scraper and click Try for free. 2. Press Start with the input empty to see the free sample row. 3. Paste links or ids into Video URLs or IDs, or type what you want into Search keywords. 4. Set Preferred transcript languages if English is not what you want. 5. Download the dataset as JSON, or pull srt out of a row and save it as a subtitle file.

💰 How much does it cost?

$0.80 per 1,000 transcripts, the same on every Apify plan.

You pay per transcript returned. The sample row, diagnostic rows and duplicate ids are never billed, so a batch of 100 videos where 12 have no captions bills 88 transcripts, not 100.

💡 What people use it for

• Turning a talk or interview into text you can search, quote and paste into notes.
• Feeding transcripts to a model for summaries, without paying a speech-to-text bill.
• Making .srt files for re-uploads, or as the starting point for a translation pass.
• Finding the exact moment a phrase was said, using segments to jump to the second.

🚧 What it does not do

• No speech to text. Published caption tracks only, auto-generated ones included. Nothing

captioned means nothing to return.

• No translation. It fetches tracks that exist. If the video has no French track, asking for

French gets you another language, not a translation.

• One video per entry. Channel and playlist links are not expanded here. There is a bulk actor

below for that.

• durationSeconds can be the transcript's length, not the video's, when YouTube returned no

metadata for that video. Sanity check it against the last segment's end if it matters.

• Metadata can be null. Title, author, view count and thumbnail come from YouTube's own

response and are sometimes absent, while the transcript itself is fine.

• Auto-generated tracks have no reliable punctuation or speaker names, and get proper nouns

wrong. isAutoGenerated is how you know which you are reading.

• Rows are large, roughly 18 to 24 KB each, because text, segments, SRT and VTT hold the same

words four ways. A 400 video run is a chunky dataset.

• Search takes YouTube's own top results. There is no filter for upload date, length or views, and

a video without captions still uses up one of the places you asked for.

• 400 videos per run in total, links and search results together.

🧭 Which YouTube scraper do you need?

❓ Questions people ask

Do I need a YouTube Data API key? No. No key, no cookies, no OAuth, no quota.

What if the video has no captions? You get an uncharged NO_TRANSCRIPT row and the batch carries on. It does not transcribe the audio.

Which language do I get? The first one in languagePreferences that exists, an exact match before a base-language one. Otherwise another available track, named in detectedLanguage.

Can I get the SRT file directly? The srt field is the file's contents. Write the string to a .srt and it plays.

Why is one video missing from my results? Look for its diagnostic row. LOGIN_REQUIRED and VIDEO_UNAVAILABLE are permanent for a signed-out reader, RATE_LIMITED is worth retrying.

Is scraping YouTube legal? This reads publicly available captions. What you then do with somebody else's words is your call, and copyright still applies. Apify's write-up on the legality of web scraping is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Include the video link and the run ID, and the errorCode on the diagnostic row if you got one.