Whisper Diarization
Whisper Large v3 Turbo combined with pyannote 4.0 for speaker diarization, returning who-said-what segments with timestamps. Built by Thomas Mol. Returns a clean JSON of speaker-labeled segments, handy for meeting notes, interviews, and podcasts.
Whisper Diarization is speech-to-text AI model from Community, priced at €0.000 per 1M input tokens with a unknown context window.
Drop audio file here
MP3, WAV, M4A, FLAC (max 25MB)
Pricing
API Integration
Use our OpenAI-compatible API to integrate Whisper Diarization into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
// Simple — just pass a string
const reply = await rw.run("whisper-diarization", "Hello! What can you do?");
console.log(reply);
// With message history
const reply2 = await rw.run("whisper-diarization", [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);
// Full response with usage info
const res = await rw.chat("whisper-diarization", [
{ role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);Frequently asked questions
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