LexiLingo

Welcome to MY PROJECT Lexilingo! This project provides several Natural Language Processing (NLP) features, including translation and language detection, POS tagging and NER recognition, text summarization, and sentiment analysis.

Features

1. Translation & Language Detection: Translate text between different languages and detect the language of the given text.
2. POS Tagging & NER Recognition: Perform Part-of-Speech (POS) tagging and Named Entity Recognition (NER) on the given text.
3. Text Summarization: Generate a concise summary of the provided text.
4. Sentiment Analysis: Analyze the sentiment of the given text to determine if it is positive, negative, or neutral.

Installation

Prerequisites

• Python 3.6 or higher
• pip (Python package installer)

Steps

1. Clone the repository:

   git clone https://github.com/your-username/nlp-project.git
   cd nlp-project

2. Create and activate a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install the required dependencies:

   pip install -r requirements.txt

4. Download NLTK data (if not already downloaded):

   import nltk
   nltk.download('punkt')
   nltk.download('vader_lexicon')

Usage

1. Start the Flask application:

   python main.py

2. Open your web browser and navigate to http://localhost:5000.

3. Use the navigation links on the homepage to access the different NLP features.

Project Structure

nlp-project/
│
├── templates/
│ ├── index.html
│ ├── translation.html
│ ├── pos_ner.html
│ ├── summarization.html
│ └── sentiment_analysis.html
│
├── static/
│
├── main.py
├── translation.py
├── pos_ner.py
├── summarization.py
└── sentiment_analysis.py

• templates/: Contains HTML templates for the web pages.
• static: Contains CSS files for styling.
• main.py: The main Flask application file.
• translation.py: Contains code for translation and language detection.
• pos_ner.py: Contains code for POS tagging and NER recognition.
• summarization.py: Contains code for text summarization.
• sentiment_analysis.py: Contains code for sentiment analysis.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Make sure to follow the existing code style and include appropriate tests.

Acknowledgments

• NLTK
• TextBlob
• spaCy