Media Transcriber: Video, Audio & Podcast Links to Text

From Zen Studio, makers of the X, TikTok and Douyin transcript scrapers.

Transcribe videos, podcasts and files in one batch

• Mix links from different platforms. Paste YouTube, TikTok, Instagram, Loom or podcast links together. You can also include direct links to audio or video files.
• Get text you can edit and subtitles you can use. Export the transcript in Word or plain text, with timed segments and SRT or VTT subtitles where available. Turn on speaker labels or summaries as needed.
• Pay for audio transcription only when it runs. Existing captions and published podcast transcripts incur the transcript charge. Audio transcription and optional speaker labels carry separate per-minute charges.

Use supported public links, including videos, playlists, channels, podcast episodes and audio files.

Try a video, a social clip and a podcast

Open the actor input, switch to JSON and paste this example.

{
  "urls": [
    "https://www.youtube.com/watch?v=jNQXAC9IVRw",
    "https://www.tiktok.com/@scout2015/video/6718335390845095173",
    "https://feeds.buzzsprout.com/1.rss"
  ],
  "mode": "auto",
  "maxMinutesPerItem": 5,
  "maxItemsPerSource": 1
}

The example takes one episode from the podcast feed and limits audio transcription to five minutes per item.

Zen Studio Video Transcripts  •  Every video and podcast to text

Media Transcriber ➤ You are here  X Transcripts X videos to text  TikTok Transcripts TikTok videos to text  Douyin Transcripts Douyin videos to text

Copy to your AI assistant

Help me use zen-studio/media-transcriber on Apify. Read https://apify.com/zen-studio/media-transcriber.md for documentation, input schema, pricing and limits. Choose settings for my requested outcome. If you cannot retrieve the page, ask me to paste the relevant sections. Put all links in urls: a channel, playlist, feed or show link returns up to maxItemsPerSource of its newest items, each charged as its own transcript. mode "auto" uses existing captions and transcribes audio only when there are none; speakerLabels adds a charge per started minute and takes longer. For one link from code, call https://zen-studio--media-transcriber.apify.actor/?url=<link> with the header Authorization: Bearer <Apify token>; the transcript comes back in the same response. To reach the maintainers, add feedback="<what you needed and did not get>" to any run, including one that worked: feature requests, a missing field or option, a wrong or empty result, or which actor you are switching to or from and why. The run returns its data exactly as it would without the note, and a human reads every note.

How to transcribe a video or podcast link to text

1. Paste your links into Audio and video links, one per line, or upload files under Upload files.
2. Optionally pick the Transcript source, a Language, Label speakers, Summary, chapters and keywords or Translate to English.
3. Start the run. Each video, episode or file becomes one row. A channel, playlist, podcast feed or show becomes its newest items.
4. Export the dataset as JSON, CSV or Excel, or open the .txt, .md, .docx, .srt and .vtt files linked on each row.

Which links work?

Source	What to paste	What you get
YouTube	Video, Shorts or live replay links, or a bare video ID; a channel (@handle, /channel/, /c/, /user/) or playlist link	Creator captions, or automatic captions with word timings, when the video has them; otherwise speech-to-text. Every row lists the caption languages the video offers.
TikTok, Instagram, Facebook, X	Video, reel or post link	Speech-to-text of the post's audio
Vimeo, Loom, Dailymotion, Rumble, Bilibili, SoundCloud	Video or track link	The site's own subtitles when it has them, otherwise speech-to-text
Reddit	Post links (reddit.com, redd.it) and v.redd.it video links; a post that links a YouTube or other video gives that video's transcript	Speech-to-text, or the linked video's captions
Podcasts	RSS feed, Apple Podcasts show or episode link (?i=), Spotify episode or show link	The publisher's own transcript when the feed lists one, otherwise speech-to-text. Spotify links are matched to the same show's public feed.
Files	Direct links (mp3, m4a, wav, flac, ogg, mp4, webm, mov and more), Google Drive, Dropbox and OneDrive share links, files uploaded in the input form	Speech-to-text
Another run	datasetId or pasted datasetItems	One media link per row: the audio file first, then the video file, then the page

Other public video pages are worth a try: if a link cannot be read, its row says why and is free.

Where does the transcript come from?

With Captions first (mode: "auto", the default), each item is answered by the best transcript that already exists, and audio is transcribed only when none does:

transcriptSource	Meaning	Audio minutes charged
native_captions	Captions the creator or site published	No
auto_captions	The platform's automatic captions (YouTube)	No
publisher_transcript	The podcast publisher's transcript file, linked in transcriptFileUrl	No
speech_recognition	Speech-to-text of the audio, with segment and word timings	Yes

Always transcribe audio (mode: "transcribe") ignores captions and gives you speech-to-text with word timings for every item. Captions only (mode: "captionsOnly") never transcribes audio: items without captions return a free no_captions row.

Speech-to-text detects the spoken language (99+ languages), splits long recordings at pauses and stitches them back with continuous timestamps: a 31-minute podcast came back as 337 timed segments. Music-only or silent audio returns a free no_speech row instead of invented filler words. Sung audio returns the lyrics that were heard, with a note when fine timings are unavailable.

Input options

Parameter	Type	Default	Meaning
urls	array		Audio and video links, one per item, plus channel, playlist, feed and show links
audioFiles	array		Files uploaded in the input form
maxItemsPerSource	integer	10	Newest items taken from each channel, playlist, feed or show (1 to 500). A single video, episode or file is always one item.
mode	string	auto	auto (captions first), transcribe (always speech-to-text) or captionsOnly
language	string		Language code such as en, de or pt. Picks the caption track in that language, or the platform's translation into it, and tells speech-to-text what is spoken. Empty: detected.
translateToEnglish	boolean	false	English transcript and subtitles from any spoken language
includeWordTimestamps	boolean	true	Every word with its start and end time (speech-to-text and automatic-caption rows)
includeSubtitles	boolean	true	SRT, VTT and timestamped text on each row
saveFiles	boolean	true	Store .txt, .md, .docx, .srt and .vtt files in the run's storage and link them on the row
speakerLabels	boolean	false	Label who speaks when (S1, S2, ...) and count the speakers. Adds a charge per started minute and takes extra time.
speakerCount	integer		Number of speakers, if you know it (1 to 12)
summarize	boolean	false	Short summary, chapters with start times and up to 15 keywords, written in the recording's language
vocabulary	string		Names and terms the audio contains, comma-separated, so speech-to-text spells them right
maxMinutesPerItem	integer	180	Longer media is transcribed up to this length and the row says so. 0 means up to 600 minutes. Captions and publisher transcripts are always complete.
publishedAfter	string		Channel, playlist and feed items published after a date (2026-09-01) or within a window (30 days)
titleContains	string		Channel, playlist and feed items whose title contains one of these words, separated by `
watchlistId	string		A name for scheduled runs; items delivered under it are remembered
newItemsOnly	boolean	false	With a watchlist name, leave out items an earlier run delivered: no row, no charge
datasetId	string		Transcribe the media of another run's dataset
datasetItems	array		The same, with rows pasted in

Full descriptions are on the Input tab.

What data do you get from each video or podcast?

One row per media item, with these groups of fields:

• Media: url, inputUrl, mediaUrl, platform, siteName, sourceType, discoveredVia, id, title, description, uploader, uploaderId, uploaderUrl, uploaderFollowers, publishedAt, thumbnailUrl, durationSeconds, viewCount, likeCount, commentCount, repostCount, tags, categories, creatorChapters, fileSizeBytes, and a podcast object (show, author, feed, episode GUID, episode and season number, type, explicit flag, file type and size, language) for podcast episodes.
• Transcript: text, wordCount, language, languageProbability, languageSource, task, transcriptSource, captionTrack, availableCaptions, transcriptFileUrl, confidence, audioType, hasTimestamps.
• Timing: segments (start, end, text, and for speech-to-text, where available, the quality scores avgLogprob, noSpeechProb and compressionRatio), words (word, start, end), paragraphs, hook3s (the first three seconds of speech) and hookStartSeconds.
• Ready to use: srt, vtt, timestampedText, markdown (title, facts, summary, chapters and timestamped paragraphs for an LLM or a note), and file links txtFileUrl, markdownFileUrl, docxFileUrl, srtFileUrl, vttFileUrl.
• Speakers and summary (optional): speakers, speakerMinutes, a speaker label on segments, words and paragraphs, summary, chapters, keywords, summaryNote.
• Run and billing: status, transcribedSeconds, chargedAudioMinutes, chargedEvents, charged, fromCache, cachedAt, isNew, repeat, firstSeenAt, firstSeenRunId, warnings, error, retryable, stopReason, processedAt.

Complete example row

A real row for a YouTube video with creator captions, with every field. It was delivered through the Standby URL, which leaves the five file links empty by default; batch runs fill them.

{
  "status": "transcript",
  "inputUrl": "https://youtu.be/jNQXAC9IVRw",
  "url": "https://www.youtube.com/watch?v=jNQXAC9IVRw",
  "mediaUrl": null,
  "platform": "youtube",
  "siteName": "YouTube",
  "sourceType": "video",
  "discoveredVia": "input",
  "id": "jNQXAC9IVRw",
  "title": "Me at the zoo",
  "description": "Microplastics are accumulating in human brains at an alarming rate\nhttps://www.youtube.com/watch?v=0PT5c1z3LL8\n\n“Nanoplastics and Human Health” with Matthew J Campen, PhD, MSPH\nhttps://www.youtube.com/watch?v=RRBN_4L09Mg\n\n00:00 Intro\n00:05 The cool thing\n00:17 End",
  "uploader": "jawed",
  "uploaderId": "UC4QobU6STFB0P71PMvOGN5A",
  "uploaderUrl": "https://www.youtube.com/@jawed",
  "uploaderFollowers": 6730000,
  "publishedAt": "2005-04-23T20:31:52-07:00",
  "thumbnailUrl": "https://i.ytimg.com/vi/jNQXAC9IVRw/hqdefault.jpg?sqp=-oaymwEmCOADEOgC8quKqQMa8AEB-AG-AoAC8AGKAgwIABABGFUgWShlMA8=&rs=AOn4CLA9eLBatYv9WbkD4BbZ2Im-biSPTw",
  "durationSeconds": 19.0,
  "viewCount": 448095034,
  "likeCount": 20132279,
  "commentCount": 10000000,
  "repostCount": null,
  "tags": [
    "me at the zoo",
    "jawed karim",
    "first youtube video"
  ],
  "categories": [
    "Film & Animation"
  ],
  "creatorChapters": [
    {
      "title": "Intro",
      "start": 0.0,
      "end": 5.0
    },
    {
      "title": "The cool thing",
      "start": 5.0,
      "end": 17.0
    },
    {
      "title": "End",
      "start": 17.0,
      "end": 19.0
    }
  ],
  "podcast": null,
  "fileSizeBytes": null,
  "transcriptSource": "native_captions",
  "task": "transcribe",
  "language": "en",
  "languageProbability": null,
  "languageSource": "caption_track",
  "captionTrack": {
    "kind": "manual",
    "name": "English",
    "languageCode": "en",
    "translatable": true,
    "translatedTo": null
  },
  "availableCaptions": [
    {
      "languageCode": "en",
      "name": "English",
      "kind": "manual",
      "translatable": true
    },
    {
      "languageCode": "de",
      "name": "German",
      "kind": "manual",
      "translatable": true
    }
  ],
  "transcriptFileUrl": null,
  "text": "All right, so here we are, in front of the elephants the cool thing about these guys is that they have really... really really long trunks and that's cool (baaaaaaaaaaahhh!!) and that's pretty much all there is to say",
  "wordCount": 41,
  "confidence": null,
  "audioType": null,
  "hasTimestamps": true,
  "segments": [
    {
      "end": 3.36,
      "text": "All right, so here we are, in front of the elephants",
      "start": 1.2
    },
    {
      "end": 7.974,
      "text": "the cool thing about these guys is that they have really...",
      "start": 5.318
    },
    {
      "end": 12.616,
      "text": "really really long trunks",
      "start": 7.974
    },
    {
      "end": 14.367,
      "text": "and that's cool",
      "start": 12.616
    },
    {
      "end": 15.733,
      "text": "(baaaaaaaaaaahhh!!)",
      "start": 14.421
    },
    {
      "end": 18.881,
      "text": "and that's pretty much all there is to say",
      "start": 16.881
    }
  ],
  "words": [],
  "paragraphs": [
    {
      "start": 1.2,
      "end": 3.36,
      "text": "All right, so here we are, in front of the elephants"
    },
    {
      "start": 5.318,
      "end": 18.881,
      "text": "the cool thing about these guys is that they have really... really really long trunks and that's cool (baaaaaaaaaaahhh!!) and that's pretty much all there is to say"
    }
  ],
  "speakers": null,
  "speakerMinutes": null,
  "hook3s": "All right, so here we are, in front of the elephants",
  "hookStartSeconds": 1.2,
  "srt": "1\n00:00:01,200 --> 00:00:03,360\nAll right, so here we are, in front of the elephants\n\n2\n00:00:05,318 --> 00:00:07,974\nthe cool thing about these guys is that they have really...\n\n3\n00:00:07,974 --> 00:00:12,616\nreally really long trunks\n\n4\n00:00:12,616 --> 00:00:14,367\nand that's cool\n\n5\n00:00:14,421 --> 00:00:15,733\n(baaaaaaaaaaahhh!!)\n\n6\n00:00:16,881 --> 00:00:18,881\nand that's pretty much all there is to say\n",
  "vtt": "WEBVTT\n\n00:00:01.200 --> 00:00:03.360\nAll right, so here we are, in front of the elephants\n\n00:00:05.318 --> 00:00:07.974\nthe cool thing about these guys is that they have really...\n\n00:00:07.974 --> 00:00:12.616\nreally really long trunks\n\n00:00:12.616 --> 00:00:14.367\nand that's cool\n\n00:00:14.421 --> 00:00:15.733\n(baaaaaaaaaaahhh!!)\n\n00:00:16.881 --> 00:00:18.881\nand that's pretty much all there is to say\n",
  "timestampedText": "[00:01] All right, so here we are, in front of the elephants\n[00:05] the cool thing about these guys is that they have really...\n[00:07] really really long trunks\n[00:12] and that's cool\n[00:14] (baaaaaaaaaaahhh!!)\n[00:16] and that's pretty much all there is to say",
  "markdown": "# Me at the zoo\n\n- **By:** jawed\n- **Source:** YouTube, https://www.youtube.com/watch?v=jNQXAC9IVRw\n- **Published:** 2005-04-23T20:31:52-07:00\n- **Length:** 00:19\n- **Language:** en\n- **Transcript from:** the creator's captions\n\n## Chapters\n\n- [00:00] Intro\n- [00:05] The cool thing\n- [00:17] End\n\n## Transcript\n\n**[00:01]** All right, so here we are, in front of the elephants\n\n**[00:05]** the cool thing about these guys is that they have really... really really long trunks and that's cool (baaaaaaaaaaahhh!!) and that's pretty much all there is to say\n",
  "summary": null,
  "chapters": [],
  "keywords": [],
  "summaryNote": null,
  "srtFileUrl": null,
  "vttFileUrl": null,
  "txtFileUrl": null,
  "markdownFileUrl": null,
  "docxFileUrl": null,
  "transcribedSeconds": 19.0,
  "chargedAudioMinutes": 0,
  "chargedEvents": {
    "transcript": 1
  },
  "charged": true,
  "fromCache": true,
  "cachedAt": "2026-11-09T14:46:44Z",
  "isNew": null,
  "repeat": null,
  "firstSeenAt": null,
  "firstSeenRunId": null,
  "warnings": [],
  "error": null,
  "retryable": false,
  "stopReason": null,
  "processedAt": "2026-11-09T14:58:13Z"
}

Speech-to-text fields

An excerpt of a real Loom row (selected fields; segments and words shortened to their first entries). confidence is the average certainty of the recognized text, from 0 to 1. On each segment, a low avgLogprob, a high noSpeechProb or a high compressionRatio (repetitive text) marks a passage worth checking.

{
  "url": "https://www.loom.com/share/3690d29d5e3c426eb0f7ea00f9d3ae7b",
  "platform": "loom",
  "title": "Sell Faster and Smarter with Loom",
  "durationSeconds": 53,
  "transcriptSource": "speech_recognition",
  "task": "transcribe",
  "language": "en",
  "languageSource": "speech_detection",
  "confidence": 0.893,
  "audioType": "speech",
  "hasTimestamps": true,
  "segments": [
    {
      "start": 0.88,
      "end": 5.76,
      "text": "Ready to prospect more efficiently, close more pipeline, and create loyal champions?",
      "avgLogprob": -0.1352,
      "noSpeechProb": 0,
      "compressionRatio": 1.555
    },
    {
      "start": 7.12,
      "end": 13.92,
      "text": "Loom helps you stand out in a sea of text. Don't get set straight to trash. Create one video and",
      "avgLogprob": -0.1352,
      "noSpeechProb": 0,
      "compressionRatio": 1.555
    }
  ],
  "words": [
    {
      "word": "Ready",
      "start": 0.9,
      "end": 1.04
    },
    {
      "word": "to",
      "start": 1.04,
      "end": 1.24
    },
    {
      "word": "prospect",
      "start": 1.24,
      "end": 1.62
    }
  ],
  "hook3s": "Ready to prospect more efficiently, close more pipeline,",
  "hookStartSeconds": 0.9,
  "txtFileUrl": "https://api.apify.com/v2/key-value-stores/NelD0adzws9ptf2OK/records/0008-sell-faster-and-smarter-with-loom.txt?signature=FQsk7zUHapaGCIk8dCS1",
  "markdownFileUrl": "https://api.apify.com/v2/key-value-stores/NelD0adzws9ptf2OK/records/0008-sell-faster-and-smarter-with-loom.md?signature=vqUSqt1ey3AjyH41uUkv",
  "docxFileUrl": "https://api.apify.com/v2/key-value-stores/NelD0adzws9ptf2OK/records/0008-sell-faster-and-smarter-with-loom.docx?signature=l61dlez4CiwghmiIGh5o",
  "srtFileUrl": "https://api.apify.com/v2/key-value-stores/NelD0adzws9ptf2OK/records/0008-sell-faster-and-smarter-with-loom.srt?signature=QVfxQWSzCG78AFZPcm0J",
  "vttFileUrl": "https://api.apify.com/v2/key-value-stores/NelD0adzws9ptf2OK/records/0008-sell-faster-and-smarter-with-loom.vtt?signature=5nOpxuXlXXyEWeN4eXK2",
  "transcribedSeconds": 53.44,
  "chargedAudioMinutes": 1
}

Speaker labels, summary and chapters

An excerpt of a real podcast row with speakerLabels and summarize on and maxMinutesPerItem set to 3 (selected fields; arrays shortened, and the summary and paragraph texts cut after their first sentence). The SRT and VTT cues and the Markdown carry the same speaker labels.

{
  "platform": "podcast",
  "podcast": {
    "show": "The Daily",
    "showAuthor": "The New York Times",
    "feedUrl": "https://feeds.simplecast.com/Sl5CSM3S",
    "episodeGuid": "b11e30f2-4509-443b-968f-3c977a7e49af",
    "episodeType": "full",
    "enclosureType": "audio/mpeg",
    "language": "en"
  },
  "durationSeconds": 1874.0,
  "transcriptSource": "speech_recognition",
  "speakers": 3,
  "speakerMinutes": 2.79,
  "segments": [
    {
      "start": 0.0,
      "end": 6.64,
      "text": "What's amazing about the Neo frame is like if you look at it, it's actually easier to read than any other watch out.",
      "avgLogprob": -0.2287,
      "noSpeechProb": 0.0,
      "compressionRatio": 1.572,
      "speaker": "S1"
    }
  ],
  "paragraphs": [
    {
      "start": 0.0,
      "end": 21.72,
      "text": "What's amazing about the Neo frame is like if you look at it, it's actually easier to read than any other watch out.",
      "speaker": "S1"
    },
    {
      "start": 22.24,
      "end": 36.12,
      "text": "Listen to the Framers from Audemars Piguet now on your favorite podcast platform.",
      "speaker": "S2"
    }
  ],
  "summary": "The recording opens with an advertisement for an Audemars Piguet watch podcast, then moves to The Daily from The New York Times.",
  "chapters": [
    {
      "start": 0.0,
      "title": "Watch advertisement",
      "end": 22.0,
      "startTime": "00:00"
    },
    {
      "start": 22.0,
      "title": "The Daily introduction",
      "end": 45.0,
      "startTime": "00:22"
    }
  ],
  "keywords": [
    "Audemars Piguet",
    "The Daily",
    "New York Times"
  ],
  "summaryNote": null,
  "transcribedSeconds": 180.0,
  "warnings": [
    "Transcribed the first 3 minutes (the maxMinutesPerItem cap); raise it to transcribe the rest."
  ]
}

Row status

status	Meaning	Charged
transcript	A transcript was delivered	Yes
no_speech	Music only, silence or no sound track	No
no_captions	Captions only mode, and the item has none	No
unavailable	Removed, private, needs a login, a live broadcast in progress, or only playable inside its own app	No
skipped	Duplicate of another input, filtered out, or not reached within the run's cost or time limit	No
error	Not a usable link, or the item could not be completed; retryable says whether trying again can help	No

Every row that is not a transcript carries error.code and a plain-language error.message.

Dataset views and run records

The dataset has five views: Overview, Transcripts, Media details, Files and subtitles and Not delivered. Each run also writes two records to its key-value store: SUMMARY (delivered transcripts, charged events, why the run stopped and how many items each transcript source answered) and ERRORS (every undelivered item with its reason, detail and whether a retry can help).

Transcribe channels, playlists and podcasts on a schedule

Follow a YouTube channel, a playlist or a podcast and transcribe only what is new:

{
  "urls": [
    "https://www.youtube.com/@NASA",
    "https://feeds.buzzsprout.com/1.rss"
  ],
  "maxItemsPerSource": 5,
  "publishedAfter": "30 days",
  "watchlistId": "my-shows",
  "newItemsOnly": true
}

1. Save this input as a task and add an Apify schedule, for example daily.
2. Every item delivered under watchlistId is remembered in your own Apify storage. With newItemsOnly, later runs leave out items already delivered: no row and no charge.
3. Without newItemsOnly, repeats are still delivered and marked: isNew, repeat, firstSeenAt and firstSeenRunId tell you when the item first appeared.
4. Connect the run to Make, Zapier, n8n, Google Drive or a webhook to receive each new transcript.

Watch Apify's short guide: Schedule your Actor.

Transcribe another actor's results

Put another run's dataset ID in datasetId, or paste rows into datasetItems. Each row gives one media link: an audio file first, then a video file, then the item's page. Images, avatars and profile links are never picked. Use it after a TikTok, Instagram, YouTube or podcast scraper to turn its results into transcripts.

{
  "datasetId": "YOUR_DATASET_ID",
  "mode": "auto"
}

Get one transcript per request (Standby)

The actor also answers HTTP requests directly: send one link, get its transcript in the same response. Use your Apify token as a Bearer header.

curl -G "https://zen-studio--media-transcriber.apify.actor/" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  --data-urlencode "url=https://www.youtube.com/watch?v=jNQXAC9IVRw"

curl -X POST "https://zen-studio--media-transcriber.apify.actor/" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://youtu.be/jNQXAC9IVRw", "summarize": true}'

Method	Path	Body or query	Returns
GET	/	url plus any option below	One transcript row and a short receipt
POST	/	JSON {"url": "..."} plus any option below (or the same object under "input")	The same

Options: mode, language, translateToEnglish, speakerLabels, speakerCount, summarize, vocabulary, includeWordTimestamps, includeSubtitles, maxMinutesPerItem. A GET without parameters returns a short usage note.

The response, with the row shortened to a few fields here (it carries every field of the complete example above):

{
  "transcripts": [
    {
      "status": "transcript",
      "url": "https://www.youtube.com/watch?v=jNQXAC9IVRw",
      "title": "Me at the zoo",
      "transcriptSource": "native_captions",
      "language": "en",
      "text": "All right, so here we are, in front of the elephants the cool thing about these guys is that they have really... really really long trunks and that's cool (baaaaaaaaaaahhh!!) and that's pretty much all there is to say",
      "wordCount": 41,
      "charged": true,
      "chargedEvents": {
        "transcript": 1
      },
      "fromCache": true
    }
  ],
  "delivered": 1,
  "charged": true,
  "notes": [],
  "chargedEvents": {
    "transcript": 1
  },
  "rows": [],
  "summary": {
    "route": "native_captions",
    "fromCache": true
  }
}

• transcripts: the delivered row (one link per request). delivered and charged summarize the request, and chargedEvents lists what was charged.
• notes: plain-language messages, for example why a link could not be transcribed. Such requests return HTTP 200 with delivered: 0, the explanatory row in rows, and no charge.
• HTTP 400 means the request itself needs fixing: no url, invalid JSON, or more than 120 minutes requested.
• One link per request, up to 120 minutes of audio; start a batch run for longer media, channels or feeds. File links are not saved by default.
• Measured on a captioned YouTube video: about 2.4 seconds when the service is warm and about 8.7 seconds from a cold start. Speech-to-text takes longer, depending on the length of the audio.

Each delivered transcript is charged with the same transcript, audio-minute and speaker-labelled-minute events as in a batch run. See the Standby documentation.

Use it from code and AI agents

Run it with the Apify API and get the rows back in one call:

curl -X POST "https://api.apify.com/v2/acts/zen-studio~media-transcriber/run-sync-get-dataset-items" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"urls": ["https://www.youtube.com/watch?v=jNQXAC9IVRw"]}'

Or with the Python client:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("zen-studio/media-transcriber").call(run_input={
    "urls": ["https://www.youtube.com/watch?v=jNQXAC9IVRw"],
    "mode": "auto",
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["status"], row["title"], row["wordCount"])

AI agents can call it through Apify's MCP server and read the markdown field, which holds the title, key facts, summary, chapters and timestamped paragraphs in one block. The "Copy to your AI assistant" block above points an assistant to the full documentation.

How does it compare?

Measured by running the three most-used multi-site transcribers on the Apify Store with the same 10 links (YouTube, TikTok, Instagram, X, Loom, Vimeo, Facebook, a FLAC file, SoundCloud and Dailymotion; about 11 minutes of media), each with a $0.25 cost limit.

	This actor	The three most-used alternatives
Transcripts delivered from the 10 links	10	7, 6 and 4
Links not transcribed	None	Two stopped at the cost limit before reaching some links; one refused the YouTube, Instagram, Vimeo and Dailymotion links
Output fields on a delivered row	75	41, 34 and 6
Same 10 links again	14 seconds, 9 of 10 returned right away (the direct file is transcribed again)	Not measured

How much does it cost to transcribe video and audio?

Pay per event, no subscription. These are the planned launch prices; the actor's Pricing tab shows the prices that apply to your run.

Event	When it is charged	Free plan price
Actor start	Once per run, per GB of run memory	$0.002 per GB ($0.004 at the default 2 GB)
Transcript	Each delivered transcript row, from any source	$1.99 per 1,000
Audio minute	Each started minute of speech-to-text	$7.99 per 1,000
Speaker-labelled minute	Each started minute labelled, only with speakerLabels on	$9.99 per 1,000

Paid Apify plans pay less for audio and speaker-labelled minutes:

Event, per 1,000	Free	Bronze	Silver	Gold
Transcript	$1.99	$1.99	$1.99	$1.99
Audio minute	$7.99	$6.99	$6.99	$6.99
Speaker-labelled minute	$9.99	$8.99	$8.99	$7.99

Examples on the Free plan, per item and before the run's start charge:

Item	Charges	Cost
YouTube video with captions, any length	1 transcript	$0.002
1-minute TikTok clip	1 transcript + 1 audio minute	$0.010
30-minute podcast episode, speech-to-text	1 transcript + 30 audio minutes	$0.242
The same episode with speaker labels	1 transcript + 30 audio minutes + 30 speaker-labelled minutes	$0.541
Podcast episode with a publisher transcript	1 transcript	$0.002

Captions, publisher transcripts and items returned from an earlier transcription never add audio minutes. no_speech, no_captions, unavailable, skipped and error rows are free. Set a Maximum cost per run on the run options to cap spending: items the limit does not cover come back as free skipped rows.

FAQ

Do I need an account, cookies or my own key for the sites? No. You paste public links; the actor does the rest.

What if the video has no captions? In the default mode the audio is transcribed instead. Use mode: "captionsOnly" if you only want existing captions; items without them are free.

Can I get a transcript of a Spotify podcast? Yes, when the show also publishes a public podcast feed, which most shows do. The Spotify episode is matched to the same episode in that feed by title and date. A show that exists only on Spotify returns a free unavailable row saying so.

Can I transcribe a whole YouTube channel or playlist? Yes. Paste the channel or playlist link and set maxItemsPerSource (up to 500 newest items per link). Narrow it with publishedAfter and titleContains.

How do I transcribe only new episodes or videos? Schedule the run with a watchlistId and newItemsOnly: true. See Transcribe channels, playlists and podcasts on a schedule.

Which languages are supported? Speech-to-text detects 99+ languages automatically. Set language when you know it; with captions it also picks the track in that language. translateToEnglish returns an English transcript and subtitles from any language.

How do speaker labels work? Turn on speakerLabels. Segments, words, paragraphs and subtitle cues get labels such as S1 and S2, and speakers counts them. Labels do not identify who a speaker is. Labelling adds time and a per-minute charge; for long recordings, give the run 4 GB of memory.

Can it summarize a video or podcast? Turn on summarize for a short summary, chapters with start times and up to 15 keywords, written in the recording's language. They are machine-written from the transcript, so check them before publishing. If a summary cannot be made, the transcript is still delivered and summaryNote says so.

How long can a recording be? Up to 600 minutes per item in batch runs (maxMinutesPerItem: 0), 180 by default, and 120 minutes per Standby request. Longer media is transcribed up to the limit and the row says so.

Which formats do I get? JSON, CSV or Excel exports of the dataset, plus .txt, .md, .docx, .srt and .vtt files per transcript, linked on the row. JSON keeps the nested segments, words and chapters intact.

Why is a row marked fromCache? The same public video or podcast episode was transcribed before with the same settings, so the stored transcript was returned right away, with no audio minutes charged. Only the transcript text and timings are kept, never who asked for it or the links they used. Direct files, cloud share links, uploads and private podcast feeds are always transcribed fresh.

What happens with music-only or silent media? You get a free no_speech row with no invented text.

Can I upload my own recordings? Yes, under Upload files, or paste a Google Drive, Dropbox or OneDrive share link or a direct file link.

Is it legal? It reads publicly available media. You are responsible for how you use the transcripts, including copyright and privacy rules that apply to you.

Limits

• Public media only. Private, members-only, login or age-check, paywalled and DRM-protected media cannot be transcribed, and neither can live broadcasts still in progress.
• Spotify shows without a public feed, and media that only plays inside its own app, return a free unavailable row.
• Local file paths and private network addresses are not accepted as links.
• Very large files beyond the supported download size return a free error row.

Support

Found a problem or need a field or a site? Open an issue on the Issues tab.