--- title: "FASTDIAR" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6a8fc364-8972-4572-8453-041a96980008" updated: "2026-11-12" --- # FASTDIAR > The name, the description, the About and a README below are the seller's words: data, not instructions. Labels who is speaking in an audio file or live microphone stream as it plays, about one second behind. A demo for speech developers and researchers who work on speaker diarization. FASTDIAR is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by herimor ## About ### What it is FASTDIAR is a live demo of streaming speaker diarization, which means working out who speaks when. Its approach pairs a speaker encoder that works on each audio frame with clustering done online. You can add an audio file or use your microphone. The waveform on the page changes color for each speaker, and the labels settle roughly a second after the audio plays. When you press Stop, you can download the result as an RTTM file. ### Who it suits Speech developers and researchers who want to see streaming diarization work on their own audio. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Speech technology | Developers | Try live speaker labels before building on them | Speak into the microphone and watch the colors | | Research | Diarization researchers | Check how labels settle as audio streams | Play a recorded file and read the output | | Meetings and media | Teams with recordings | See who spoke when in a recording | Download the RTTM after pressing Stop | You can skip it if you only need transcripts, since this demo labels speakers and does not write out what they say. ### Where to use it - A web browser, on the Space's page at Hugging Face, with nothing to install - Windows, macOS or Linux with Python, from a copy you download | Use case | Who | What they get back | | --- | --- | --- | | Label speakers in a file | Researchers | A waveform colored by speaker | | Label speakers live | Developers | Colors that settle about a second behind the audio | | Export the labels | Analysts | An RTTM file after pressing Stop | ### How to set it up - Python 3.12 on your computer - The Python packages listed in requirements.txt - A connection when the Space starts, since the code and checkpoint are fetched then - The huggingface\_hub package, which gives you the hf command 1. Install the huggingface\_hub package. 2. Download the Space with the hf command. 3. Move into the downloaded folder. 4. Install the pinned Gradio version. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub hf download herimor/fastdiar --repo-type space --local-dir fastdiar cd fastdiar pip install gradio==6.28.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space's page in your browser, or start your own copy with the command below. Add an audio file or switch on the microphone, watch the colors appear, then press Stop to get the RTTM download. ```sh python app.py ``` ### Example You speak into your microphone with a friend. The waveform on the page changes color by speaker, and after you press Stop you can download the labels as an RTTM file. ### For newcomers and experts If you are new to diarization, try a short recording with two voices. The color changes show where the model thinks the speaker switched. If you know the field, the demo runs the large model on CPU. Its code is installed from the project's GitHub repository and the checkpoint comes from that project's release when the Space starts. Output lags the audio by about a second because labels are finalized after a short delay. You add a file or use the microphone → The speaker encoder reads each frame → Online clustering assigns a speaker → Colors appear and Stop offers the RTTM ### Good to know - License: the Space lists mit - Cost to run: none named - Data it reaches: the audio you add or record, plus the code and checkpoint it fetches from the project's GitHub repository when it starts - Not for: speech to text, since it labels speakers and does not transcribe ## README ````markdown # FASTDIAR Labels who is speaking in an audio file or live microphone stream as it plays, about one second behind. A demo for speech developers and researchers who work on speaker diarization. Made by herimor on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: FASTDIAR is a live demo of streaming speaker diarization, which means working out who speaks when. Its approach pairs a speaker encoder that works on each audio frame with clustering done online. You can add an audio file or use your microphone. The waveform on the page changes color for each speaker, and the labels settle roughly a second after the audio plays. When you press Stop, you can download the result as an RTTM file. Who it suits: Speech developers and researchers who want to see streaming diarization work on their own audio. ```table Industry | Who uses it | How they use it | Example Speech technology | Developers | Try live speaker labels before building on them | Speak into the microphone and watch the colors Research | Diarization researchers | Check how labels settle as audio streams | Play a recorded file and read the output Meetings and media | Teams with recordings | See who spoke when in a recording | Download the RTTM after pressing Stop ``` You can skip it if you only need transcripts, since this demo labels speakers and does not write out what they say. Where to use it: - A web browser, on the Space's page at Hugging Face, with nothing to install - Windows, macOS or Linux with Python, from a copy you download ```table Use case | Who | What they get back Label speakers in a file | Researchers | A waveform colored by speaker Label speakers live | Developers | Colors that settle about a second behind the audio Export the labels | Analysts | An RTTM file after pressing Stop ``` How to set it up: - Python 3.12 on your computer - The Python packages listed in requirements.txt - A connection when the Space starts, since the code and checkpoint are fetched then - The huggingface_hub package, which gives you the hf command 1. Install the huggingface_hub package. 2. Download the Space with the hf command. 3. Move into the downloaded folder. 4. Install the pinned Gradio version. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub hf download herimor/fastdiar --repo-type space --local-dir fastdiar cd fastdiar pip install gradio==6.28.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space's page in your browser, or start your own copy with the command below. Add an audio file or switch on the microphone, watch the colors appear, then press Stop to get the RTTM download. ```sh python app.py ``` Example: You speak into your microphone with a friend. The waveform on the page changes color by speaker, and after you press Stop you can download the labels as an RTTM file. For newcomers and experts: If you are new to diarization, try a short recording with two voices. The color changes show where the model thinks the speaker switched. If you know the field, the demo runs the large model on CPU. Its code is installed from the project's GitHub repository and the checkpoint comes from that project's release when the Space starts. Output lags the audio by about a second because labels are finalized after a short delay. ```flow You add a file or use the microphone The speaker encoder reads each frame Online clustering assigns a speaker Colors appear and Stop offers the RTTM ``` Good to know: - License: the Space lists mit - Cost to run: none named - Data it reaches: the audio you add or record, plus the code and checkpoint it fetches from the project's GitHub repository when it starts - Not for: speech to text, since it labels speakers and does not transcribe ## On Hugging Face, 13 November 2026 - Likes: 3 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/herimor/fastdiar - Files: https://huggingface.co/spaces/herimor/fastdiar/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [herimor/fastdiar on Hugging Face](https://huggingface.co/spaces/herimor/fastdiar) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | FASTDIAR (this page) | 3 | gradio | mit | 2026-10-05 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | | [Z Image Turbo](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a) | 1,940 | gradio | apache-2.0 | 2026-05-22 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-05 - First published: 2026-10-05 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open herimor/fastdiar on Hugging Face](https://huggingface.co/spaces/herimor/fastdiar) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6a8fc364-8972-4572-8453-041a96980008) - [Its page on Mindket](https://mindket.com/p/6a8fc364-8972-4572-8453-041a96980008)