readme.txt

---
title: Accent Classifier
emoji: 🎙️
colorFrom: indigo
colorTo: cyan
sdk: gradio
sdk_version: "3.38.1"
app_file: app.py
pinned: false
---

# Accent Classifier 🎙️

This Gradio app downloads a public YouTube or Vimeo video, extracts its audio, and classifies the speaker (as a proxy for accent) using a Hugging Face model. It’s perfect for demonstrating how to hook up **yt-dlp**, **ffmpeg**, and a **wav2vec2** pipeline in one slick interface—no rocket science required (just a little AI eavesdropping).

---

## 🛠️ How It Works

1. **Input**: You paste a *public* YouTube or Vimeo video URL into the Gradio textbox.  
2. **Download**: Under the hood, `yt-dlp` fetches the video’s best audio stream and saves it as `downloaded_video.mp4`.  
3. **Extract Audio**: `ffmpeg` converts that MP4 into a WAV file (`extracted_audio.wav`) at 16 kHz, mono—exactly what speech models crave.  
4. **Classify**: A Hugging Face `pipeline("audio-classification", model="superb/wav2vec2-base-superb-sid")` processes the WAV file and returns a speaker ID (used here as an accent proxy) plus confidence.  
5. **Cleanup**: Temporary files are removed automatically so you don’t end up with a cluttered folder.  
6. **Output**: The app displays the predicted speaker ID and confidence percentage.  

---

## 📦 Requirements

- **Python 3.8+**  
- **yt-dlp** (installed automatically by the script if missing)  
- **ffmpeg** (must be installed on your system and accessible via your command line)  
- **gradio** (for the web interface)  
- **transformers** (Hugging Face library)  

> ❗ **Note**: If `yt-dlp` is not already installed, the code will install it at runtime. However, you must have `ffmpeg` installed manually. On macOS you can use Homebrew (`brew install ffmpeg`); on Ubuntu/Debian, `sudo apt-get install ffmpeg`; on Windows, download from [ffmpeg.org](https://ffmpeg.org/) and add it to your PATH.

---

## 🚀 Installation

1. **Clone or Download** this repository (the one containing `app.py` and this `README.md`).  
2. **(Optional)** Create and activate a virtual environment:

   ```bash
   python3 -m venv venv
   source venv/bin/activate    # macOS/Linux
   venv\Scripts\activate.bat   # Windows