README.md

---
title: H2O Wave Whisper
emoji: 🎙🔊
colorFrom: yellow
colorTo: gray
sdk: docker
app_port: 7860
duplicated_from: h2oai/h2o_wave_whisper
---

<div align='center'>

<h1>WaveTon</h1>
💯 Wave applications

<br>
<br>

[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg?logo=apache)](https://github.com/vopani/waveton/blob/master/LICENSE)
[![GitHub](https://img.shields.io/github/stars/vopani/waveton?color=yellowgreen&logo=github)](https://img.shields.io/github/stars/vopani/waveton?color=yellowgreen&logo=github)
[![Twitter](https://img.shields.io/twitter/follow/vopani)](https://twitter.com/vopani)

</div>

## Whisper 🖥️

Speech to text using OpenAI's Whisper model.

![](demo.gif)

## Setup ⚙️

1. Check the version of Python, must be Python 3.9+ but recommended to use Python 3.10+ for best experience

```commandline
python3 --version
```

2. Clone the repository

```commandline
git clone https://github.com/vopani/waveton.git
```

3. Create a virtual environment

```commandline
cd waveton/apps/deeplearning_apps/whisper
python3 -m venv venv
source venv/bin/activate
```

4. Install ffmpeg

On Linux:

```commandline
sudo apt update && sudo apt install ffmpeg
```

On Mac:

```commandline
brew install ffmpeg                         
```

5. Install the packages

```commandline
python3 -m pip install -U pip
python3 -m pip install -r requirements.txt
```

6. Run the application

```commandline
wave run app
```

7. View the application on your local browser: [http://localhost:10101](http://localhost:10101)