# Audio & Video to Text — AI Transcript API (Whisper) (`adorable_partial/whisper-audio-video-transcriber`) Actor

Transcribe audio & video to text in bulk with OpenAI Whisper AI. Paste file links, Google Drive/Dropbox or podcast RSS feeds → transcripts with timestamps + SRT/VTT subtitles. 99 languages, auto-detect, translate to English. From $0.006/min, no API key.

- **URL**: https://apify.com/adorable\_partial/whisper-audio-video-transcriber.md
- **Developed by:** [Leandro Zanatta](https://apify.com/adorable_partial) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.00 / 1,000 audio minute (fast)s

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 to Text — AI Transcript API (Whisper)

Turn any **audio or video file into text** with **OpenAI Whisper**, in bulk, without an API key or a GPU. Paste links to MP3, MP4, WAV, M4A and other media files, share links from Google Drive or Dropbox, or whole **podcast RSS feeds**. You get clean **transcripts with timestamps** and ready-to-use **SRT and VTT subtitles**.

- 🌍 **99 languages**, with automatic language detection
- 🇬🇧 **Translate to English** from any supported language
- ⏱️ **Segment and word-level timestamps**
- 🎬 **SRT / VTT subtitle files** for every transcript
- 📡 **Podcast transcription** straight from RSS feeds
- 📦 **Bulk transcription**: hundreds of files in one run
- 💸 **From $0.006 per minute**, and you only pay for audio that was transcribed successfully

### What does this speech-to-text Actor do?

It downloads each media file, runs Whisper speech recognition on it and saves the result to a dataset: full transcript text, detected language, duration, timestamped segments and links to SRT/VTT subtitle files. Export as JSON, CSV, Excel or HTML, or fetch it through the API.

Typical uses:

- **Podcast transcripts**: show notes, blog posts, SEO articles and searchable archives
- **Video subtitles and captions** for courses, webinars, YouTube uploads and social clips
- **Meeting, interview and lecture transcription**
- **AI and LLM pipelines**: feed spoken content into RAG, summarisation, chatbots and AI agents
- **Content repurposing**: turn audio and video into text, quotes and social posts

### How to transcribe audio or video to text

1. Paste one or more file URLs into **Audio / video URLs**, or podcast feeds into **Podcast RSS feeds**.
2. Choose a **Quality** (see below). Leave **Language** empty to auto-detect it.
3. Click **Start**. When the run finishes, open the **Output** tab to see the transcripts and download the subtitles.

### Quality levels and pricing

You pay per started minute of transcribed audio. Failed files are free.

| Quality | Whisper model | Price per minute | 1-hour podcast | Best for |
|---|---|---|---|---|
| Fast | base | $0.006 | $0.36 | Clear speech, large volumes |
| Balanced (default) | small | $0.015 | $0.90 | Podcasts, interviews, meetings |
| Accurate | large-v3-turbo | $0.07 | $4.20 | Accents, noisy audio, names and jargon, non-English |

There is also a small start fee per run ($0.00125 per GB of memory, about $0.005 with the default 4 GB). Set **Max duration per file** or a maximum cost per run to stay within budget: the Actor stops transcribing when the limit is reached.

### Supported inputs

- **Audio:** MP3, M4A, AAC, WAV, FLAC, OGG, OPUS, WMA
- **Video:** MP4, MOV, WEBM, MKV, AVI (the audio track is transcribed)
- **Links:** any direct, publicly downloadable URL, plus public **Google Drive** and **Dropbox** share links
- **Podcasts:** any standard podcast **RSS feed**; the newest N episodes are transcribed

### Input example

```json
{
  "mediaUrls": ["https://github.com/openai/whisper/raw/main/tests/jfk.flac"],
  "rssFeeds": ["https://feeds.npr.org/510289/podcast.xml"],
  "maxEpisodesPerFeed": 2,
  "quality": "balanced",
  "language": "",
  "translateToEnglish": false,
  "wordTimestamps": false
}
```

### Output example

```json
{
  "sourceUrl": "https://github.com/openai/whisper/raw/main/tests/jfk.flac",
  "language": "en",
  "languageProbability": 0.98,
  "durationSeconds": 11.0,
  "transcribedSeconds": 11.0,
  "truncated": false,
  "text": "And so, my fellow Americans, ask not what your country can do for you, ask what you can do for your country.",
  "srtUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-0001.srt",
  "vttUrl": "https://api.apify.com/v2/key-value-stores/.../records/transcript-0001.vtt",
  "segments": [
    {
      "start": 0.0,
      "end": 11.0,
      "text": "And so, my fellow Americans, ask not what your country can do for you, ask what you can do for your country.",
      "words": [{ "start": 0.0, "end": 0.52, "word": "And" }, { "start": 0.52, "end": 0.82, "word": "so" }]
    }
  ]
}
```

`words` is only included when **Word-level timestamps** is on.

### Use it as a transcription API

Call the Actor from your code with the Apify API or client libraries:

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("adorable_partial/whisper-audio-video-transcriber").call(
    run_input={"mediaUrls": ["https://example.com/interview.mp3"], "quality": "balanced"}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["text"])
```

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

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('adorable_partial/whisper-audio-video-transcriber').call({
    mediaUrls: ['https://example.com/interview.mp3'],
    quality: 'balanced',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0].text);
```

It also works with **Make, Zapier, n8n**, webhooks and scheduled runs, and as a tool for **AI agents** (Claude, ChatGPT, Cursor…) through the Apify MCP server.

### FAQ

**Which languages are supported?**
All 99 Whisper languages, including English, Spanish, Portuguese, French, German, Italian, Hindi, Japanese, Chinese, Arabic and Russian. The language is detected automatically, or you can set it.

**Do I need an OpenAI API key?**
No. Whisper runs inside the Actor, and you only pay the per-minute price.

**Can it transcribe YouTube, TikTok or Instagram links?**
No. It needs a direct link to a media file (or a podcast RSS feed). Only process content you have the right to use.

**How long can a file be?**
Up to 4 GB per file. Use **Max duration per file** to transcribe only the first N minutes.

**How accurate is it?**
Accurate mode (large-v3-turbo) is close to the best open speech recognition models available. Fast and Balanced trade some accuracy for a lower price and are usually enough for clear speech.

**How fast is it?**
Fast mode handles about 4 minutes of audio per minute of runtime at the default 4 GB of memory. For Accurate mode on long files, give the run 8–16 GB of memory (more CPU cores).

**Is speaker diarization included?**
Not yet. If you need speaker labels, open an issue.

### Tips

- Set **Language** when you know it: detection is skipped and short clips come out more accurate.
- Use **Translate to English** to get English subtitles for foreign-language video.
- Found a bug or need a feature? Open an issue in the **Issues** tab.

# Actor input Schema

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

Direct links to audio or video files (mp3, m4a, wav, ogg, flac, mp4, webm, mov...). Public Google Drive and Dropbox share links are supported.

## `rssFeeds` (type: `array`):

Podcast RSS feed URLs. The newest episodes of each feed are transcribed.

## `maxEpisodesPerFeed` (type: `integer`):

How many of the newest episodes to transcribe from each RSS feed.

## `quality` (type: `string`):

fast = Whisper base (cheapest), balanced = Whisper small, accurate = Whisper large-v3-turbo (best accuracy, slowest).

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

ISO 639-1 code of the spoken language (e.g. en, pt, es). Leave empty to auto-detect.

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

Output an English translation instead of the original-language transcript.

## `includeSegments` (type: `boolean`):

Add a list of segments with start/end times to each result.

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

Add start/end times for every word inside each segment (great for karaoke-style captions, editing and search). Slightly slower.

## `maxDurationMinutes` (type: `integer`):

Only the first N minutes of each file are transcribed. Protects you from unexpectedly long files.

## Actor input object example

```json
{
  "mediaUrls": [
    "https://github.com/openai/whisper/raw/main/tests/jfk.flac"
  ],
  "maxEpisodesPerFeed": 1,
  "quality": "balanced",
  "translateToEnglish": false,
  "includeSegments": true,
  "wordTimestamps": false,
  "maxDurationMinutes": 180
}
```

# Actor output Schema

## `transcripts` (type: `string`):

One item per file: text, language, duration, subtitle links and timestamped segments.

## `transcriptsFull` (type: `string`):

All fields including timestamped segments.

## `subtitles` (type: `string`):

SRT and VTT subtitle files, one pair per transcribed file.

# 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://github.com/openai/whisper/raw/main/tests/jfk.flac"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("adorable_partial/whisper-audio-video-transcriber").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://github.com/openai/whisper/raw/main/tests/jfk.flac"] }

# Run the Actor and wait for it to finish
run = client.actor("adorable_partial/whisper-audio-video-transcriber").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://github.com/openai/whisper/raw/main/tests/jfk.flac"
  ]
}' |
apify call adorable_partial/whisper-audio-video-transcriber --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,adorable_partial/whisper-audio-video-transcriber"
        }
    }
}
```

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/Lwe1BIbk1KmueN9q9/builds/71EOGTkGZs86BOqHJ/openapi.json