# Audio & Video Transcription: Whisper, Podcasts, SRT/VTT (`swiftkit/transcribe`) Actor

- **URL**: https://apify.com/swiftkit/transcribe.md
- **Developed by:** [SwiftKit](https://apify.com/swiftkit) (community)
- **Categories:** AI, Videos, Agents
- **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 audio minutes

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Audio & Video Transcription: Whisper, Podcasts, SRT/VTT

Turn audio and video files into text with **OpenAI's Whisper** speech recognition (open-source
model, run on Apify's servers: no API key, no OpenAI account). For each file you get:

- **Full transcript text** and **word count**
- **Timestamped segments** (start, end, text): ready for search, chaptering or quoting
- **SRT and VTT subtitle files** (download links)
- **Language detected automatically** (90+ languages) with a confidence score, or set it yourself
- **Translate to English:** English text from speech in any language (Whisper's built-in translation)
- **Word-level timestamps** (optional): start, end and confidence for every word, for captions and editing
- **Duration** and the minutes billed

**Inputs it accepts:**

- Direct links to audio or video files: mp3, m4a, aac, wav, flac, ogg, opus, mp4, mov, webm, mkv…
- **Podcast RSS feeds:** transcribes the latest episodes
- **Apple Podcasts links:** finds the show's feed and transcribes the latest episodes

Silent files, files with no speech, unreachable links and files that can't be decoded are **not
charged**.

### Who it's for

- **Podcasters and creators:** show notes, subtitles, blog posts and quotes from episodes.
- **Researchers and journalists:** searchable text of interviews, lectures and recordings.
- **AI and RAG pipelines:** feed spoken content into LLMs, summaries and search.
- **Accessibility:** captions for your own videos (SRT/VTT).

### Input

| Option | Default | What it does |
|---|---|---|
| Audio/video files or podcasts | – | File links, RSS feeds or Apple Podcasts links |
| Accuracy | Balanced | Fast (Whisper tiny), Balanced (base), Accurate (small) |
| Language | auto | Two-letter code to skip detection, e.g. `en`, `ja` |
| Translate to English | off | English output from any language |
| Word-level timestamps | off | Per-word timing and confidence |
| Podcasts: episodes per feed | 1 | Latest N episodes per feed |
| Max minutes per file | 180 | Longer files are skipped (not charged) |
| Save SRT and VTT subtitle files | on | Links in each result |

### Output

A real result (LibriVox public-domain recording of the Gettysburg Address):

```json
{
  "url": "https://archive.org/download/gettysburg_address_librivox/gettysburg_address_lincoln_64kb.mp3",
  "status": "ok",
  "language": "en",
  "languageProbability": 0.998,
  "durationSec": 161,
  "billedMinutes": 3,
  "model": "base",
  "processingSec": 36.6,
  "wordCount": 328,
  "text": "This is a Libravox Recording. All Libravox recordings are in the public domain. ... The address set the dedication of the National Cemetery at Gettysburg, November 19, 1863, ...",
  "segments": [{ "start": 0.0, "end": 4.5, "text": "This is a Libravox Recording." }],
  "srtUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-001.srt",
  "vttUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-001.vtt"
}
```

Note the transcript says "Libravox": Whisper writes what it hears, and names can come out
slightly wrong. The Accurate setting helps.

Other statuses: `unreachable`, `no_speech`, `too_long`, `not_supported`, `over_budget`, `error`.
None are charged.

### Use it from your AI agent (MCP)

Claude, Cursor and other MCP clients can call this tool directly through Apify's MCP server. Add it as
an MCP server / connector:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=swiftkit/transcribe",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}
```

Then just ask, for example: *"Transcribe this episode and give me the five main points: https://…/episode.mp3"*. Each call is billed like a normal run.

### Pricing

- A small fee **per run** (loading the speech model)
- **Per audio minute** transcribed, rounded up per file. Fast and Balanced cost the same. Accurate
  needs about 3x the computing power, so each minute counts as 3.

See the Pricing tab. With 2 CPU cores (the default 8 GB memory), Balanced transcribes about **8x
faster than real time**: a 60-minute episode takes about 7–8 minutes.

### Limits, honestly

- **Only files you're allowed to use.** Transcribe your own recordings, public-domain or licensed
  material, or podcasts for personal or research use. Respect copyright.
- **Video and social platforms aren't supported** (YouTube, TikTok, Instagram, Facebook, X, Vimeo,
  Spotify…). Their terms forbid downloading. Give a direct file link instead.
- No speaker labels (who said what). Translation is into English only. Whisper is very good, not perfect: check
  names, numbers and technical terms.
- Files up to 1.5 GB and 10 hours.

### More tools from SwiftKit

- [Podcast Search & Episodes](https://apify.com/swiftkit/podcasts): find shows, episode lists with audio links, top charts
- [PDF to Text & Markdown](https://apify.com/swiftkit/pdf-text): text from PDFs for AI and RAG
- [Website to Markdown for AI](https://apify.com/swiftkit/web-to-markdown): clean page content for LLMs

### Questions?

Open an issue on the Issues tab.

# Actor input Schema

## `mediaUrls` (type: `array`):

Direct links to audio or video files (mp3, m4a, wav, mp4, webm…), podcast RSS feeds, or Apple Podcasts links. Feeds and Apple links transcribe their latest episodes. Video and social platforms (YouTube, TikTok…) are not supported.

## `model` (type: `string`):

Bigger models are more accurate and slower. Fast and Balanced cost the same per minute; Accurate uses about 3x the computing power, so each minute counts as 3.

## `language` (type: `string`):

Two-letter code such as en, es, ja. Leave empty to detect automatically.

## `translateToEnglish` (type: `boolean`):

Output English text for speech in any language (Whisper's built-in translation). Same price. "language" in the result is the spoken language.

## `wordTimestamps` (type: `boolean`):

Add start/end time and confidence for every word (for captions, karaoke-style subtitles and editing). Slightly slower, same price.

## `episodesPerFeed` (type: `integer`):

Latest episodes to transcribe for each feed or Apple link.

## `maxMinutesPerFile` (type: `integer`):

Longer files are skipped (not charged).

## `saveSrtVtt` (type: `boolean`):

Links to subtitle files in each result.

## Actor input object example

```json
{
  "mediaUrls": [
    "https://archive.org/download/gettysburg_address_librivox/gettysburg_address_lincoln_64kb.mp3"
  ],
  "model": "base",
  "translateToEnglish": false,
  "wordTimestamps": false,
  "episodesPerFeed": 1,
  "maxMinutesPerFile": 180,
  "saveSrtVtt": true
}
```

# Actor output Schema

## `results` (type: `string`):

One row per file or episode.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mediaUrls": [
        "https://archive.org/download/gettysburg_address_librivox/gettysburg_address_lincoln_64kb.mp3"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("swiftkit/transcribe").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "mediaUrls": ["https://archive.org/download/gettysburg_address_librivox/gettysburg_address_lincoln_64kb.mp3"] }

# Run the Actor and wait for it to finish
run = client.actor("swiftkit/transcribe").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "mediaUrls": [
    "https://archive.org/download/gettysburg_address_librivox/gettysburg_address_lincoln_64kb.mp3"
  ]
}' |
apify call swiftkit/transcribe --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,swiftkit/transcribe"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/uEVyhFs2rb1ho4IeY/builds/GSLs1r6prroeWdBNJ/openapi.json