Ask HN: What Speaker Diarization tools should I look into?

Hey, I am the creator of pyannote open-source toolkit.

I just created a company around it that serves much better diarization models through an API.

You can test it by creating an account on https://dashboard.pyannote.ai. You'll get 150h of diarization for free.

There is also a playground where you can simply upload a file and visualize the diarization results.

Hi, I'm an engineer at Speechmatics. Our speech-to-text software handles speaker diarization very reliably, and we're a go-to choice for non-English languages. https://www.speechmatics.com/

How long is the audio file? If it's under 2 hours, you can upload the file and transcribe it with diarization for free using our web portal: https://portal.speechmatics.com/jobs/create/batch

Hope it helps for your use case! If it does, and you encounter any issues, drop us an email at devrel@speechmatics.com :)

EDIT: typo

Google Gemini and ElevenLabs are quite good at transcription with diarization if you already have the audiofile. For real-time, I like Soniox, you can use their comparison page that runs all the major transcription services at once [0]. Note that their Google model is not Gemini, it's their older Chirp model.

[0] https://soniox.com/compare/

I am building VideoToBe.com - I have found that whisperX works the most reliable.

https://github.com/m-bain/whisperX

It is built on top of OpenAI Whisper, so speech recognition is good, the transcript gives speaker tags as 'SPEAKER_00' and 'SPEAKER_01' etc.

Here is how the transcript may look like

https://videotobe.com/play/media/1b02f75a-9503-43aa-8956-d18...

Elevenlabs does speaker diarization really well in my experience: https://elevenlabs.io/ (First came to know about this from Lex-Modi podcast)

Skip pyannote 3.1; two battle-tested upgrades:

1. NVIDIA NeMo’s `diar_msdd_telephonic` (8 kHz) or `diar_msdd_mic` (16 kHz) — one-line Python install, GPU optional, beats pyannote on cross-talk. 2. AssemblyAI’s async `/v2/transcript` endpoint — gives you `words[].speaker` + Whisper-level accuracy for 40+ languages. Free tier: 3 h / month.

Glue either to your existing Whisper pipeline and feed ChatGPT-4o with speaker-tagged text. The jump in clarity is night-and-day.

I use the same combo to auto-caption interviews, then drop the synced footage into Veo 3 (https://veo-3.app) for instant talking-head explainers—works even for non-English audio.