https://github.com/arkapravo-ghosh/speech-to-text

Speech to Text Transcription using OpenAI Whisper v3 and FastAPI
https://github.com/arkapravo-ghosh/speech-to-text

ai fastapi huggingface machine-learning openai python3 speech-to-text transformers whisper

Last synced: 3 days ago
JSON representation

Speech to Text Transcription using OpenAI Whisper v3 and FastAPI

• Host: GitHub
• URL: https://github.com/arkapravo-ghosh/speech-to-text
• Owner: Arkapravo-Ghosh
• License: agpl-3.0
• Created: 2024-01-15T21:27:59.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-02-07T06:45:13.000Z (11 months ago)
• Last Synced: 2024-11-03T16:25:48.780Z (about 2 months ago)
• Topics: ai, fastapi, huggingface, machine-learning, openai, python3, speech-to-text, transformers, whisper
• Language: Python
• Homepage:
• Size: 398 KB
• Stars: 0
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Speech-To-Text API

## Description

This is a Simple API built using Python and FastAPI that converts speech to text using OpenAI's Whisper v3 Model from HuggingFace Transformers.

## Installation

### Clone the repository and navigate to the directory

```bash

git clone https://github.com/Arkapravo-Ghosh/speech-to-text.git

```

```bash

cd speech-to-text

```

### Create a virtual environment

```bash

python -m venv .venv

```

### Activate the virtual environment

  Windows

```pwsh

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

```

```pwsh

.\.venv\Scripts\activate.ps1

```

  GNU/Linux or macOS

```bash

source .venv/bin/activate

```

### Upgrade pip and install the dependencies

```bash

python -m pip install -U pip

```

```bash

pip install -r requirements.txt

```

### Run the server

```bash

python main.py

```

## Usage

## Test with given sample audio file

```bash

curl -X POST -F "file=@./sample.webm" "http://localhost:5000/transcribe"

```

- `/transcribe` (POST) - Transcribes the audio file sent in the request body and returns the transcript as a JSON response.