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This project aims to provide developers and researchers with a powerful tool for working with text data, including tasks such as text summarization, topic modeling, named entity recognition (NER), translation, and speech-to-text conversion.

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NLP Nexus

NLP Nexus is a comprehensive natural language processing (NLP) toolkit that combines various NLP functionalities into a single, unified platform. This project aims to provide developers and researchers with a powerful tool for working with text data, including tasks such as text summarization, topic modeling, named entity recognition (NER), translation, and speech-to-text conversion.

Features

  • Text Summarization: Generate concise summaries of textual content using state-of-the-art algorithms and techniques.
  • Topic Modeling: Uncover hidden topics within a collection of documents to gain insights and facilitate information retrieval.
  • Named Entity Recognition (NER): Identify and extract named entities such as persons, organizations, locations, and more from text.
  • Translation: Translate text between different languages using machine translation models and libraries.
  • Speech-to-Text Conversion: Convert spoken language into written text, enabling transcription and analysis of audio recordings.

Installation

1- To get started with NLP Nexus, follow these steps:

Clone the repository:

git clone https://github.com/sinanazem/nlp-nexus.git

2- Install the required dependencies:

pip install -r requirements.txt

3- Run the application:

python main.py

Usage

Once the application is running, you can access the various NLP functionalities through a user-friendly interface. Simply follow the prompts or refer to the documentation for detailed instructions on how to utilize each feature.

Contributing

Contributions to NLP Nexus are welcome! If you'd like to contribute new features, enhance existing functionality, or fix any issues, please submit a pull request. Be sure to follow the guidelines outlined in the CONTRIBUTING.md file


Contact

If you have any questions, suggestions, or feedback, please feel free to reach out to us at sinanazemm@gmail.com.


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This project aims to provide developers and researchers with a powerful tool for working with text data, including tasks such as text summarization, topic modeling, named entity recognition (NER), translation, and speech-to-text conversion.

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