--- title: "Automatic Speech Recognition" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/9a56dc27-8868-4010-9ce4-6c804112f4d9" updated: "2026-11-12" --- # Automatic Speech Recognition > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo from the k2-fsa project that turns speech audio into text. It names six speech models, including Vosk Russian models and icefall models, and runs on CPU. Automatic Speech Recognition is a kit in the Productivity 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 k2-fsa ## About ### What it is This Space is an automatic speech recognition demo from the k2-fsa project. It turns speech audio into written text. The repository names six speech models, two Vosk models with ru in their names and four icefall models, and it runs on basic CPU hardware at Hugging Face. ### Who it suits People who want to try speech to text models without installing anything, and developers who want a small example of several recognizers behind one Gradio page. Speech researchers can see which named models the demo covers. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Speech technology | Speech engineers | Try the named recognizers on their own audio | Running one recording through the demo and reading the text | | Media | Editors and journalists | Turn a spoken recording into rough text | Getting a first transcript of an interview clip | | Software | Python developers | Read app.py, decode.py and model.py to see how the models are called | Copying the Space to add another model | | Research | Students of speech recognition | Compare what the named models produce | Hearing how LibriSpeech-trained models handle a clip | If you never work with speech audio, you can skip it. ### Where to use it - A web browser, on the Space's page at Hugging Face - Windows with Python 3.10.0 - macOS with Python 3.10.0 - Linux with Python 3.10.0 | Use case | Who | What they get back | | --- | --- | --- | | Transcribe a recording | Anyone with speech audio | The text the model hears | | Try several recognizers | Engineers and students | A demo that covers the six models it names | ### How to set it up Online use needs nothing. A copy on your own computer needs a little. - Python 3.10.0 on Windows, macOS or Linux - The pip tool, to install the packages from requirements.txt - Nothing at all if you use the Space online, since it runs in the browser 1. Install the Hugging Face hub package. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install Gradio at the pinned version, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download k2-fsa/automatic-speech-recognition --repo-type space --local-dir automatic-speech-recognition cd automatic-speech-recognition pip install gradio==5.25.2 pip install -r requirements.txt python app.py ``` ### How to use it Online, open the Space's page and use the app there. On your own computer, run this command from the project folder and open the page Gradio shows. The repository also holds a test\_wavs folder of sample audio. ```sh python app.py ``` ### Example You open the Space and give it a speech recording. The app turns the recording into text and shows you what it heard. ### For newcomers and experts If you are new to this, open the Space's page and try one of the sample recordings, if the page offers them. Nothing needs installing, and you see what speech to text looks like. If you know the field, the six named models are two Vosk models with ru in their names, an icefall MGB2 conformer CTC model and three icefall LibriSpeech pruned transducer models. The code is split into app.py, decode.py, model.py and examples.py, and the hosted copy runs on CPU, so long recordings may be slow. Open the Space or run app.py locally → Give the app a speech recording → A named model decodes the audio → You read the text it returns ### Good to know The source says little beyond the model names, so check the results on your own audio. - License: Apache 2.0, as the Space's license line says - Cost to run: none named, and the hosted copy uses cpu-basic hardware at Hugging Face - Data it reaches: the audio you give it, and the six speech models it names, which are hosted on Hugging Face ## README ````markdown # Automatic Speech Recognition A Gradio demo from the k2-fsa project that turns speech audio into text. It names six speech models, including Vosk Russian models and icefall models, and runs on CPU. Made by k2-fsa 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: This Space is an automatic speech recognition demo from the k2-fsa project. It turns speech audio into written text. The repository names six speech models, two Vosk models with ru in their names and four icefall models, and it runs on basic CPU hardware at Hugging Face. Who it suits: People who want to try speech to text models without installing anything, and developers who want a small example of several recognizers behind one Gradio page. Speech researchers can see which named models the demo covers. ```table Industry | Who uses it | How they use it | Example Speech technology | Speech engineers | Try the named recognizers on their own audio | Running one recording through the demo and reading the text Media | Editors and journalists | Turn a spoken recording into rough text | Getting a first transcript of an interview clip Software | Python developers | Read app.py, decode.py and model.py to see how the models are called | Copying the Space to add another model Research | Students of speech recognition | Compare what the named models produce | Hearing how LibriSpeech-trained models handle a clip ``` If you never work with speech audio, you can skip it. Where to use it: - A web browser, on the Space's page at Hugging Face - Windows with Python 3.10.0 - macOS with Python 3.10.0 - Linux with Python 3.10.0 ```table Use case | Who | What they get back Transcribe a recording | Anyone with speech audio | The text the model hears Try several recognizers | Engineers and students | A demo that covers the six models it names ``` How to set it up: Online use needs nothing. A copy on your own computer needs a little. - Python 3.10.0 on Windows, macOS or Linux - The pip tool, to install the packages from requirements.txt - Nothing at all if you use the Space online, since it runs in the browser 1. Install the Hugging Face hub package. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install Gradio at the pinned version, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download k2-fsa/automatic-speech-recognition --repo-type space --local-dir automatic-speech-recognition cd automatic-speech-recognition pip install gradio==5.25.2 pip install -r requirements.txt python app.py ``` How to use it: Online, open the Space's page and use the app there. On your own computer, run this command from the project folder and open the page Gradio shows. The repository also holds a test_wavs folder of sample audio. ```sh python app.py ``` Example: You open the Space and give it a speech recording. The app turns the recording into text and shows you what it heard. For newcomers and experts: If you are new to this, open the Space's page and try one of the sample recordings, if the page offers them. Nothing needs installing, and you see what speech to text looks like. If you know the field, the six named models are two Vosk models with ru in their names, an icefall MGB2 conformer CTC model and three icefall LibriSpeech pruned transducer models. The code is split into app.py, decode.py, model.py and examples.py, and the hosted copy runs on CPU, so long recordings may be slow. ```flow Open the Space or run app.py locally Give the app a speech recording A named model decodes the audio You read the text it returns ``` Good to know: The source says little beyond the model names, so check the results on your own audio. - License: Apache 2.0, as the Space's license line says - Cost to run: none named, and the hosted copy uses cpu-basic hardware at Hugging Face - Data it reaches: the audio you give it, and the six speech models it names, which are hosted on Hugging Face ## On Hugging Face, 13 November 2026 - Likes: 60 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition - Files: https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition/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 [k2-fsa/automatic-speech-recognition on Hugging Face](https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition) ## 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 | | --- | --- | --- | --- | --- | | Automatic Speech Recognition (this page) | 60 | gradio | apache-2.0 | 2026-11-06 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | 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: 2026-11-06 - First published: 2025-04-21 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open k2-fsa/automatic-speech-recognition on Hugging Face](https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/9a56dc27-8868-4010-9ce4-6c804112f4d9) - [Its page on Mindket](https://mindket.com/p/9a56dc27-8868-4010-9ce4-6c804112f4d9)