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---
title: Accent Classifier
emoji: 🚀
colorFrom: red
colorTo: red
sdk: docker
app_port: 8501
tags:
- streamlit
pinned: false
short_description: Streamlit template space
---
# English Accent Detector (SpeechBrain)
This Streamlit app detects English accents from speech in public video URLs using the SpeechBrain accent classification model.
---
## Features
- Input a public video URL (MP4, Loom, etc.)
- Downloads the video
- Extracts up to 60 seconds of audio
- Classifies English accent with confidence score
- Provides an explanation of the detected accent
---
## Requirements
- Python 3.12 or higher
- ffmpeg installed and available in PATH (required by `moviepy`)
- Internet connection (to download videos and model weights)
---
## Setup
1. **Clone the repo** (or copy your project files):
```bash
git clone https://github.com/Kedar43/accent_detector.git
cd accent_detector
```
2. **Create and activate a virtual environment (optional but recommended):**
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install dependencies:**
```bash
pip install -r requirements.txt
```
---
## Usage
Run the Streamlit app:
```bash
streamlit run app.py
```
- This will open a browser window/tab with the app interface.
- Paste a public video URL (must be MP4).
- Wait while the app downloads the video and processes audio (up to 60 seconds).
- View the detected English accent, confidence score, and explanation.
---
## Testing the app
- Use sample public MP4 videos containing English speech with distinct accents.
- The app logs runtime info and errors to app.log in the working directory.
- If errors occur, check app.log for detailed traceback and messages.
---
## Notes
- The SpeechBrain model is loaded once and cached to improve performance on repeated runs.
- Temporary video and audio files are deleted automatically after processing.
- Accuracy depends on the quality of audio and the SpeechBrain model’s training data.
- Make sure video URLs are publicly accessible without authentication. |