Podcast Transcriber: Podcast & Audio to Text, MP3, SRT, VTT

Try it free: Apify's free plan includes monthly platform credit, no credit card needed. One example run with the input below costs about $0.02 (the ~3-minute Gettysburg Address recording, transcribed without your own API key at $0.006 per audio minute).

{
  "mediaUrls": [
    "https://archive.org/download/gettysburg_shurtagal_librivox/Gettysburg_Address_Lincoln_64kb.mp3"
  ],
  "transcriptionProvider": "managed",
  "confirmRights": true
}

Paste this into the JSON tab of the input form and click Start.

Get a podcast transcript for any episode: turn podcast episodes and audio files into searchable text (podcast to text and audio to text with Whisper speech to text). Give the Actor one or more podcast RSS feeds, Apple Podcasts links or direct audio/video links (MP3, M4A, WAV, MP4 and more) and get, for every episode, the full transcript, timestamped segments with word timestamps, and ready-made TXT, SRT, VTT and JSON files.

Run it on a schedule with "Only new episodes" and it transcribes each new episode exactly once - a simple podcast monitor for media monitoring, research, show notes and podcast SEO.

What you get

• 🎙️ Podcast RSS feeds or audio URLs - mp3, m4a, wav, ogg, mp4, webm and more
• 🆕 Only new episodes since the last run - remembers what it already transcribed (per monitor name)
• 📝 Full text + segments with start/end times, word-level timestamps when available
• 📄 Files per episode: plain text (TXT), subtitles (SRT, WebVTT) and a JSON file with every word timestamp
• 🌍 Many languages with automatic language detection (Whisper)
• ⚡ Three engines: fast Groq Whisper large-v3-turbo with no API key needed, Groq with your own Groq API key (lowest price), or the built-in local Whisper (no third party)
• 💸 Pay only for audio you transcribe - per started audio minute, with a cost cap per episode
• 🛑 Clear error messages instead of silently empty results

Full podcast transcripts or short clips?

This Actor gives you the full plain podcast transcript of each episode, from the first word to the last. That is what you want for searching through episodes, writing notes or show notes, pulling quotes, or keeping a text archive of a podcast. It does not judge which parts are interesting.

If you are after short videos, have a look at Podcast & Video Clip Finder. It picks the strongest 20 to 60 second moments of an episode and returns them ready to cut, with timestamps, subtitles for each clip and hook title ideas for TikTok, Reels and Shorts.

Get a podcast transcript from any RSS feed or Apple Podcasts link

1. Paste a podcast RSS feed URL or an Apple Podcasts show link into Podcast RSS feed URL(s) (or a direct mp3 link into Direct audio/video file URL(s)).
2. Tick "I own this audio or am allowed to transcribe it".
3. Optional: paste your own Groq API key (free at console.groq.com/keys) for the lowest price per minute. Without a key, the Actor uses Groq Whisper large-v3-turbo for you, no key needed.
4. Start. Each episode appears in the dataset; the files are linked in every item.

Free demo: leave everything empty (or keep the prefilled link) to transcribe a 63-second public-domain LibriVox recording of the Gettysburg Address. The demo needs no key and is never charged.

Podcast monitor (only new episodes)

Turn on Only new episodes since the last run, set Max episodes per feed (e.g. 3) and create a schedule (daily or weekly). Each run transcribes only episodes that earlier runs have not transcribed yet. Use Monitor name to keep separate lists, for example one per client. Failed episodes are retried on the next run.

Input example

{
  "rssFeedUrls": ["https://www.nasa.gov/feeds/podcasts/small-steps-giant-leaps"],
  "confirmRights": true,
  "maxEpisodesPerFeed": 2,
  "onlyNewEpisodes": true,
  "transcriptionProvider": "auto",
  "groqApiKey": "gsk_...",
  "outputFormats": ["txt", "srt", "vtt", "json"]
}

Output

One dataset item per episode (shortened):

{
  "episodeTitle": "Human Factors: Designing Systems with People in Mind - Part 1 of 2",
  "podcastTitle": "Small Steps, Giant Leaps",
  "publishedAt": "2026-09-16T12:34:00Z",
  "feedUrl": "https://www.nasa.gov/feeds/podcasts/small-steps-giant-leaps",
  "mediaUrl": "https://traffic.megaphone.fm/....mp3",
  "language": "en",
  "transcriptionEngine": "groq:whisper-large-v3-turbo",
  "wordTimestamps": "word",
  "mediaDurationSeconds": 1139.0,
  "transcribedSeconds": 1139.0,
  "billedAudioMinutes": 19,
  "wordCount": 2950,
  "text": "The knowledge of how human cognition systems work ...",
  "segments": [
    {"id": 0, "start": 0.72, "end": 5.6, "startTimestamp": "00:00:00.720",
     "text": "The knowledge of how human cognition systems work and how they're evolved has led to a lot",
     "words": [{"word": "The", "start": 0.74, "end": 0.86}, {"word": "knowledge", "start": 0.86, "end": 1.16}]}
  ],
  "txtUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-41b57fe93743.txt",
  "srtUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-41b57fe93743.srt",
  "vttUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-41b57fe93743.vtt",
  "jsonUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-41b57fe93743.json"
}

Also included: podcast author, episode GUID, episode page and plain-text show notes. The run's key-value store has a RUN_SUMMARY with the status of every episode, errors and billed minutes. Export the dataset as JSON, CSV, Excel or via the API.

Engines

	Groq, no key needed	Groq (your key)	Local Whisper
Model	Whisper large-v3-turbo	Whisper large-v3-turbo or large-v3	Whisper base or tiny (faster-whisper)
Speed	very fast	very fast (10 minutes of audio in about 5 seconds in our tests)	about 0.75x real time at 1 GB memory (10 min of audio in ~7.5 min); with 4 GB about 4x faster
Accuracy	best	best	good with clear English speech; names and rare words are often wrong
Who processes the audio	Groq Inc. (USA), through the Actor developer's Groq account	Groq Inc. (USA), your own account	only inside your Apify run
Limits	one rate limit shared by all users (see below)	Groq's limits for your account	max. 120 minutes per episode and what fits into the run timeout
Extra cost	none, included in the per-minute price	Groq bills your key directly (about $0.04 per audio hour at the time of writing)	none

Auto (default) uses your own Groq key when you enter one, otherwise Groq with no key needed.

No API key needed: how it works and its limits

Without a key of your own, the Actor sends the audio to Groq's Whisper large-v3-turbo using the developer's Groq account. You get the same transcript quality as with your own key and the turbo model, without signing up anywhere, at a somewhat higher price per minute.

The catch: this runs on Groq's free tier, so there is one rate limit and one daily quota that all users of the Actor share. At the moment that is roughly 2 hours of audio per hour and 8 hours of audio per day for everyone together. The Actor waits up to about two minutes when Groq is busy. If the limit is still used up, the rest of the episode is transcribed with the local Whisper engine and billed as local minutes, so you still get a complete transcript, but that part is slower and less accurate. The run's status message and the transcriptionEngine field tell you when this happened. For large batches or daily monitors, your own free Groq key is the more reliable choice. The free demo (empty input) always uses the local engine. The audio is sent to Groq Inc. in the USA (see Data protection below).

German and other non-English audio: the local engine works best for clear English speech. With the small base model, German and other languages come out noticeably less accurate, and results can vary from run to run. For German and other languages, use a Groq engine (no key needed, or your own key) and always set Spoken language.

Tip for the local engine: set the run memory to 4096 MB. It is about 4x faster and the price per audio minute stays the same. If an episode does not fit into the run timeout, the Actor delivers and bills only the part it transcribed and says so in the status message.

Skipped speech: the local engine checks its transcript for longer stretches of speech that came back without text and re-transcribes those parts with full precision (float32), at no extra charge. With the base model this second pass needs at least 2048 MB memory (at 1024 MB it runs with tiny; with base the run log only notes the gap).

Pricing (pay per event)

You pay per started audio minute that was actually transcribed - nothing for episodes that fail, are skipped or contain no speech:

• Audio minute (Groq, no key needed) - Groq Whisper large-v3-turbo through the developer's Groq account
• Audio minute (Groq, your key) - for transcription with your own Groq API key
• Audio minute (local Whisper) - for the built-in engine, which uses much more compute
• Apify's small default Actor start event

See the Pricing tab for the current prices. Max audio minutes per episode caps the cost per episode, and the run stops cleanly when your Maximum cost per run is reached (the episode in progress is shortened to fit).

Data protection (GDPR) and rights

• Only transcribe audio you are allowed to use. The Actor processes public podcast feeds and files you point it to; you confirm your rights with the checkbox and are responsible for how you use the transcripts. Transcripts of third-party podcasts are typically fine for personal research or internal monitoring but usually not for republishing.
• No YouTube, Spotify, TikTok etc. Their terms do not allow downloading media. Use the show's RSS feed or a direct file link instead. Apple Podcasts links are only used to look up the show's public RSS feed through Apple's public lookup service; the audio always comes from the publisher's own feed.
• Groq engines: the audio is sent to Groq (Groq Inc., USA) for transcription: with your own key under your own Groq account, or without a key under the developer's Groq account. The Actor never stores your audio or transcripts outside your own Apify storage. If the audio contains personal data (voices, names), you are the controller under the GDPR and need a legal basis; check Groq's terms and data processing terms for your use case, or use the local engine, which keeps the audio inside the Apify run.
• The Actor stores results only in your own Apify storage (dataset, key-value store, and for "only new episodes" a named key-value store podcast-transcriber-state that holds episode IDs). The developer has no access to your data.

FAQ

Which feeds work? Any public RSS/Atom podcast feed with audio or video enclosures (Libsyn, Anchor/Spotify for Podcasters RSS, Megaphone, Buzzsprout, Podbean, ...). If you only have an Apple Podcasts link, paste it as it is: show links go into Podcast RSS feed URL(s), episode links (with ?i=) work in either field. The Actor finds the show's public RSS feed for you. Shows that are exclusive to Apple or subscriber-only have no public feed and are skipped with a clear error, without charge.

How accurate is it? Groq's Whisper large-v3 (and large-v3-turbo, which the no-key engine uses) is among the most accurate open speech models. The local base model is fine for clear English speech; names and technical terms can be wrong. Set Spoken language if you know it.

Speaker labels? Not yet - Whisper does not identify speakers.

Can I process long episodes? Yes. Long files are split at pauses and the timestamps are stitched together. With Groq, episodes of several hours work; the local engine stops after 120 minutes per episode (use 4096 MB memory for long episodes).

Why did a run return nothing? The status message and RUN_SUMMARY always say why: no new episodes since the last run, filters matched nothing, a feed or file could not be downloaded, or the cost limit was reached.

Questions or a feed that does not work? Open an issue on the Actor page.

Further reading

• faster-whisper int8 dropped up to 60 s of speech. float32 didn't: the measurement behind the thread cap in this Actor's local engine.
• Podcast to text in Python: the same core job as a free script you run yourself (GitHub).

Related Actors by the same developer

• Podcast Transcript Scraper: pulls the transcripts podcasters already publish in their RSS feed. Cheaper and faster than transcribing when a show has them.
• Podcast & Video Clip Finder: finds the strongest short-form moments in a podcast or video and returns timestamps, hooks and SRT subtitles for each clip.