The "AI Language Detector and Translator" project is a comprehensive solution designed to accurately detect languages and translate English text to either French or Urdu based on user selection. Leveraging Python programming language and the Naive Bayes algorithm, this project caters to diverse linguistic needs by providing robust language detection and translation capabilities.
The development of this project was made possible through the contributions of the following individuals:
- Kashif Muneer (2021-CE-34)
- Mehmood Ul Haq (2021-CE-35)
- Muhammad Shahzaib (2021-CE-41)
- Talal Muzammal (2021-CE-47)
- Language Detection: The model accurately identifies the language of input text, enabling seamless processing of multilingual data.
- Translation: English text can be translated to either French or Urdu, facilitating effective communication across language barriers.
- Dataset Variety: Diverse datasets were utilized during model training to enhance accuracy and versatility.
- Python Implementation: Developed using Python programming language, ensuring flexibility and ease of maintenance.
- Naive Bayes Algorithm: The Naive Bayes algorithm is leveraged for efficient language detection and translation capabilities.
- Comprehensive Documentation: Detailed insights into dataset selection, model architecture, training methodology, and testing results are provided in the accompanying report, aiding in understanding and replicating the project.
To use the project, follow these steps:
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Clone the repository:
git clone https://github.com/your_username/ai-language-detector-translator.git
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Install the required dependencies
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Run the program:
python main.py
To utilize the AI Language Detector and Translator:
- Ensure Python is installed on your system.
- Clone the repository.
- Follow the instructions provided in the Project report for setup and usage guidelines.
Here is the complete demosntration and explanation of the complete project.
AI.Language.Detector.and.Translator.Compress.mp4
For any queries you can contact me at my email [email protected]
We acknowledge the contributions of various open-source projects and datasets that facilitated the development of this project. Additionally, we extend our gratitude to the Python community for creating and maintaining a robust ecosystem of libraries and tools.