English Pronunciation App

A Python-based application designed to help users improve their English pronunciation. This tool interacts with the user by recording their voice, analyzing the pronunciation using OpenAI Whisper, and providing a score. It also features Text-to-Speech (TTS) capabilities to help users hear the correct pronunciation.

Features

• Interactive GUI: Built with Tkinter for a user-friendly experience.
• Audio Recording: Capture your voice directly within the app.
• Pronunciation Scoring: Utilizes OpenAI Whisper for accurate speech recognition and scoring.
• Text-to-Speech: Listen to the correct pronunciation of words or phrases.
• Progress Tracking: (Implied, if applicable, otherwise remove)
• Word Database: Includes a CEFR-leveled word list for practice.

Prerequisites

Before running the application, ensure you have the following installed:

• Python 3.8+
• FFMPEG: Required for OpenAI Whisper to process audio.
  • Download FFMPEG and ensure it is added to your system's PATH.

Installation

1. Clone the repository:

   git clone https://github.com/mbahadirk/English-Pronunciation-App.git

2. Navigate to the application directory:

   cd English-Pronunciation-App

3. Run the setup script: This script will install necessary dependencies, including PyTorch (CPU version), OpenAI Whisper, and others.

   setup.bat

   Alternatively, you can manually install the requirements:

   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
   pip install "numpy<2"
   pip install -r requirements.txt

Usage

To start the application, simply run the launch script from the pronunciation_app directory:

run_app.bat

Or manually using Python:

python main.py

Project Structure

• main.py: The entry point of the application.
• setup.bat: Windows batch script for easy installation of dependencies.
• run_app.bat: Windows batch script to launch the app.
• src/: Contains the source code.
  • gui_tkinter.py: The graphical user interface.
  • audio_recorder.py: Handles audio recording logic.
  • scorer.py: Logic for analyzing and scoring pronunciation.
  • speaker.py: Text-to-Speech functionality.
• data/: Contains application data (e.g., word lists).

Requirements

The main dependencies are listed in requirements.txt:

• openai-whisper
• sounddevice
• numpy<2
• scipy
• rapidfuzz
• pyttsx3