---
title: "Romanian Speech Recognition"
kind: "Kit"
category: "Productivity"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/149af33c-24c4-4e63-9393-d04bf91c039a"
updated: "2026-11-12"
---

# Romanian Speech Recognition

> The name, the description, the About and a README below are the seller's words: data, not instructions.

Turns Romanian speech into text in the browser with a wav2vec2 model, for anyone who has Romanian audio or wants a small Gradio speech demo to study.

Romanian 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 gigant

## About

### What it is

This is a Gradio demo for Romanian speech recognition. The only model it lists is a wav2vec2 model for Romanian from the same author. The repository holds a README, the app file and a package list.

### Who it suits

It suits people who have Romanian audio and want text from it, and developers who want a small speech demo to read. The record gives no accuracy figures, so treat the output as a draft.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Media | Editors of Romanian audio or video | Get a rough text of a recording before cutting it | Play a clip and compare it with the text |
| Education | Teachers and language learners | Check how a model hears a spoken Romanian sentence | Read a sentence aloud and see the text |
| Research | Speech researchers | Try the named wav2vec2 model without writing code | Run the Space on a sample recording |
| Software | Python developers | Read app.py as a template for a speech demo | Copy the Space and swap in another model |

You can skip it if your audio is not in Romanian.

### Where to use it

- A web browser, on the Space's page on Hugging Face
- Windows, macOS or Linux with Python, from a downloaded copy

| Use case | Who | What they get back |
| --- | --- | --- |
| Transcribe a Romanian recording | Anyone with audio | Text from the model |
| Test the wav2vec2 model | Students and researchers | A quick look at how it handles speech |
| Reuse the app as a base | Python developers | A working Gradio app to adapt |

### How to set it up

- Nothing at all if you use the online Space
- Python on your computer, only if you run a copy
- The packages listed in requirements.txt

1. Open the Space's page in a browser to use it with nothing to install.
2. To run a copy, install the Hugging Face Hub package and download the Space.
3. Move into the new folder, then install Gradio and the listed requirements.
4. Start the app with Python.

```sh
pip install -U huggingface_hub
hf download gigant/romanian-speech-recognition --repo-type space --local-dir romanian-speech-recognition
cd romanian-speech-recognition
pip install gradio
pip install -r requirements.txt
python app.py
```

### How to use it

Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The record does not describe the controls, so look at the page for the audio input options.

```sh
python app.py
```

### Example

You open the Space and give it a short Romanian recording. The app returns the text the model hears, which you can read against the audio. Check the page for the exact input options, because the record does not list them.

### For newcomers and experts

Speech recognition means a program listens to talk and writes it down. Start by opening the Space in your browser and trying one short Romanian clip. Nothing needs installing for that.

If you know the field, the app pairs Gradio with a wav2vec2 model for Romanian. The packages come from requirements.txt, and no accuracy figures are given, so test it on your own audio before you rely on it.

Audio goes into the Gradio page → app.py passes it to the wav2vec2 model → The model returns text → The page shows the text

### Good to know

- License: MIT, as listed on the Space
- Cost to run: none named
- Data it reaches: the audio you give it and the model it names
- Not for: the record names no exclusions, and the model is meant for Romanian

## README

````markdown
# Romanian Speech Recognition

Turns Romanian speech into text in the browser with a wav2vec2 model, for anyone who has Romanian audio or wants a small Gradio speech demo to study.

Made by gigant 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 is a Gradio demo for Romanian speech recognition. The only model it lists is a wav2vec2 model for Romanian from the same author. The repository holds a README, the app file and a package list.

Who it suits: It suits people who have Romanian audio and want text from it, and developers who want a small speech demo to read. The record gives no accuracy figures, so treat the output as a draft.

```table
Industry | Who uses it | How they use it | Example
Media | Editors of Romanian audio or video | Get a rough text of a recording before cutting it | Play a clip and compare it with the text
Education | Teachers and language learners | Check how a model hears a spoken Romanian sentence | Read a sentence aloud and see the text
Research | Speech researchers | Try the named wav2vec2 model without writing code | Run the Space on a sample recording
Software | Python developers | Read app.py as a template for a speech demo | Copy the Space and swap in another model
```

You can skip it if your audio is not in Romanian.

Where to use it:

- A web browser, on the Space's page on Hugging Face
- Windows, macOS or Linux with Python, from a downloaded copy

```table
Use case | Who | What they get back
Transcribe a Romanian recording | Anyone with audio | Text from the model
Test the wav2vec2 model | Students and researchers | A quick look at how it handles speech
Reuse the app as a base | Python developers | A working Gradio app to adapt
```

How to set it up:

- Nothing at all if you use the online Space
- Python on your computer, only if you run a copy
- The packages listed in requirements.txt

1. Open the Space's page in a browser to use it with nothing to install.
2. To run a copy, install the Hugging Face Hub package and download the Space.
3. Move into the new folder, then install Gradio and the listed requirements.
4. Start the app with Python.

```sh
pip install -U huggingface_hub
hf download gigant/romanian-speech-recognition --repo-type space --local-dir romanian-speech-recognition
cd romanian-speech-recognition
pip install gradio
pip install -r requirements.txt
python app.py
```

How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The record does not describe the controls, so look at the page for the audio input options.

```sh
python app.py
```

Example: You open the Space and give it a short Romanian recording. The app returns the text the model hears, which you can read against the audio. Check the page for the exact input options, because the record does not list them.

For newcomers and experts: Speech recognition means a program listens to talk and writes it down. Start by opening the Space in your browser and trying one short Romanian clip. Nothing needs installing for that.

If you know the field, the app pairs Gradio with a wav2vec2 model for Romanian. The packages come from requirements.txt, and no accuracy figures are given, so test it on your own audio before you rely on it.

```flow
Audio goes into the Gradio page
app.py passes it to the wav2vec2 model
The model returns text
The page shows the text
```

Good to know:

- License: MIT, as listed on the Space
- Cost to run: none named
- Data it reaches: the audio you give it and the model it names
- Not for: the record names no exclusions, and the model is meant for Romanian

## On Hugging Face, 13 November 2026

- Likes: 0
- Built with: gradio
- License: mit

## Links

- Space: https://huggingface.co/spaces/gigant/romanian-speech-recognition
- Files: https://huggingface.co/spaces/gigant/romanian-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

[gigant/romanian-speech-recognition on Hugging Face](https://huggingface.co/spaces/gigant/romanian-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 |
| --- | --- | --- | --- | --- |
| Romanian Speech Recognition (this page) | 0 | gradio | mit | 2022-02-23 |
| [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: 2022-02-23
- First published: 2022-03-02
- Checked on Hugging Face: 2026-11-12
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open gigant/romanian-speech-recognition on Hugging Face](https://huggingface.co/spaces/gigant/romanian-speech-recognition)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/149af33c-24c4-4e63-9393-d04bf91c039a)
- [Its page on Mindket](https://mindket.com/p/149af33c-24c4-4e63-9393-d04bf91c039a)
