--- title: "English_audio_transcriptor" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a8a8084e-f5a4-4a98-ae48-d001753da1e8" updated: "2026-11-13" --- # English\_audio\_transcriptor > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns spoken English into text with the wav2vec2 base model in a Gradio page, with four example dialogue clips included. For students, developers and anyone who needs a quick transcript. English\_audio\_transcriptor is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Sakil ## About ### What it is This Gradio app from Sakil turns spoken English into text. It names one model, facebook/wav2vec2-base-960h, and the repository holds four example audio clips named after Batman and Catwoman dialogue. You use it in a browser, or you run a copy on your own computer. ### Who it suits It suits people who need a quick transcript of English audio, and students and developers who want to see a speech model at work. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media | Podcasters | Get a rough text of a short English clip | Upload a clip and read the text | | Education | Language students | Check how a speech model hears English | Try one of the example dialogue clips | | Software | Python developers | Read how a wav2vec2 model is served in Gradio | Download the Space and open app.py | Skip it if you need other languages or a polished transcript, because the model is for English and its output needs a check. ### Where to use it - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python | Use case | Who | What they get back | | --- | --- | --- | | Transcribe a clip | Podcasters | English text for a short recording | | Test the model | Students | A quick look at how it hears different voices | | Study the code | Developers | An app.py that loads one speech model | ### How to set it up You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face - Spare disk space, since the first run may need to download the model 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Sakil/english_audio_transcriptor --repo-type space --local-dir english_audio_transcriptor cd english_audio_transcriptor pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` ### Example You run python app.py inside the project folder, open the page and give it batman2\_dialogue.wav from the repository. The page returns the English text the model heard in that clip. ### For newcomers and experts If this is new to you, start online. Go to the Space and try one of the example clips before you install anything. Speech recognition means the program writes down what it hears. If you know the field, note that the Space names one wav2vec2 base model and app.py loads it, with a packages.txt beside it. The source gives no error rates, so test it on your own recordings. Open the Space or run app.py → The Gradio page loads → You give it English audio → The wav2vec2 model reads it → The text appears on the page ### Good to know Speech models can mishear names and noisy audio, so check the transcript against the recording. - License: apache-2 - Cost to run: none named, no API key, account or paid service - Data it reaches: the audio you give it and the model it names, with nothing else listed ## README ````markdown # English_audio_transcriptor Turns spoken English into text with the wav2vec2 base model in a Gradio page, with four example dialogue clips included. For students, developers and anyone who needs a quick transcript. Made by Sakil 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 Gradio app from Sakil turns spoken English into text. It names one model, facebook/wav2vec2-base-960h, and the repository holds four example audio clips named after Batman and Catwoman dialogue. You use it in a browser, or you run a copy on your own computer. Who it suits: It suits people who need a quick transcript of English audio, and students and developers who want to see a speech model at work. ```table Industry | Who uses it | How they use it | Example Media | Podcasters | Get a rough text of a short English clip | Upload a clip and read the text Education | Language students | Check how a speech model hears English | Try one of the example dialogue clips Software | Python developers | Read how a wav2vec2 model is served in Gradio | Download the Space and open app.py ``` Skip it if you need other languages or a polished transcript, because the model is for English and its output needs a check. Where to use it: - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python ```table Use case | Who | What they get back Transcribe a clip | Podcasters | English text for a short recording Test the model | Students | A quick look at how it hears different voices Study the code | Developers | An app.py that loads one speech model ``` How to set it up: You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face - Spare disk space, since the first run may need to download the model 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Sakil/english_audio_transcriptor --repo-type space --local-dir english_audio_transcriptor cd english_audio_transcriptor pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` Example: You run python app.py inside the project folder, open the page and give it batman2_dialogue.wav from the repository. The page returns the English text the model heard in that clip. For newcomers and experts: If this is new to you, start online. Go to the Space and try one of the example clips before you install anything. Speech recognition means the program writes down what it hears. If you know the field, note that the Space names one wav2vec2 base model and app.py loads it, with a packages.txt beside it. The source gives no error rates, so test it on your own recordings. ```flow Open the Space or run app.py The Gradio page loads You give it English audio The wav2vec2 model reads it The text appears on the page ``` Good to know: Speech models can mishear names and noisy audio, so check the transcript against the recording. - License: apache-2 - Cost to run: none named, no API key, account or paid service - Data it reaches: the audio you give it and the model it names, with nothing else listed ## On Hugging Face, 13 November 2026 - Likes: 2 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Sakil/english_audio_transcriptor - Files: https://huggingface.co/spaces/Sakil/english_audio_transcriptor/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 [Sakil/english_audio_transcriptor on Hugging Face](https://huggingface.co/spaces/Sakil/english_audio_transcriptor) ## 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 | | --- | --- | --- | --- | --- | | English\_audio\_transcriptor (this page) | 2 | gradio | apache-2.0 | 2023-08-06 | | [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, from 2026-11-12 to 2026-11-13. ## 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: 2023-08-06 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Sakil/english_audio_transcriptor on Hugging Face](https://huggingface.co/spaces/Sakil/english_audio_transcriptor) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a8a8084e-f5a4-4a98-ae48-d001753da1e8) - [Its page on Mindket](https://mindket.com/p/a8a8084e-f5a4-4a98-ae48-d001753da1e8)