Real-Time Speech Translation

Overview

This project demonstrates a real-time speech translation application using Python and various libraries.

Dependencies

• speech_recognition: Python library for speech recognition
• googletrans: Python wrapper for Google Translate API
• nltk: Natural Language Toolkit for NLP tasks
• numpy: Library for numerical computations
• pandas: Library for data manipulation and analysis
• Other standard Python libraries

Key Features

• Speech Recognition: Utilizes the Google Web Speech API through speech_recognition library to transcribe spoken words into text.
• Language Translation: Integrates googletrans library to translate recognized text into multiple target languages.
• Dynamic Language Selection: Supports a wide range of languages for both source and target translations.
• Ambient Noise Adjustment: Enhances accuracy by adjusting for ambient noise levels during speech recognition.

Technologies Used

• Python: Used for application development.
• Libraries: speech_recognition, googletrans, numpy, pandas, re, nltk, sklearn.
• Integrated Development Environment (IDE): Used Visual Studio Code

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Setup

1. Clone the repository:
git clone https://github.com/your-username/real-time-speech-translation.git
2. Install dependencies:
pip install -r requirements.txt
3. Run the application:
python transcribe_translate.py

Usage

Upon running the application, follow the prompts to select the source language and begin speaking for real-time translation.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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