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A newer version of the Gradio SDK is available:
5.43.1
metadata
title: Accent Classifier + Transcriber
emoji: 🎙️
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 4.20.0
app_file: app.py
pinned: false
Accent Classifier + Speech Transcriber
This Gradio app allows you to:
- Upload or link to audio/video files
- Automatically transcribe the speech (via OpenAI Whisper)
- Detect the speaker's accent (28-class Wav2Vec2 model)
- View a top-5 ranked list of likely accents with confidence scores
How to Use
Option 1: Upload an audio file
- Supported formats: .mp3, .wav
Option 2: Upload a video file
- Supported format: .mp4 (audio will be extracted automatically)
Option 3: Paste a direct .mp4 video URL
- Must be a direct video file URL (not a webpage)
- Example: a file hosted on archive.org or a CDN
Not Supported
- Loom, YouTube, Dropbox, or other webpage links (they don't serve real video files)
- Download the video manually and upload it if needed
Models Used
Transcription:
Accent Classification:
Running Locally
To set this up and run locally, follow these steps:
- Clone the repository
git clone https://huggingface.co/spaces/usamaijaz-ai/accent-classifier
cd accent-classifier
- Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install the dependencies
pip install -r requirements.txt
If there’s no requirements.txt
, use:
pip install gradio==4.20.0 transformers torch moviepy==1.0.3 requests safetensors soundfile scipy
- Install ffmpeg
- macOS:
brew install ffmpeg
- Ubuntu:
sudo apt install ffmpeg
- Windows: Download here and add to PATH
- Run the app
python app.py
- Access in your browser
Visithttp://localhost:7860
to use the app locally.
How It Works
- Audio is extracted (if input is a video)
- Audio is converted to
.wav
and resampled to 16kHz - Speech is transcribed using Whisper
- Accent is classified using a Wav2Vec2 model
- Output includes:
- Top accent prediction
- Confidence score
- Top-5 accent list
- Full transcription