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v1shal/News_Summarisation_and_Sentiment_Analysis

sourceHugging Faceupdated 2y agoView on Hugging Face

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App README

NewsSummarisationSentiment_Analysis

This is a web-based application that extracts key details from multiple news articles related to a given company, performs sentiment analysis, conducts a comparative analysis, and generates a text-to-speech (TTS) output in Hindi.

Features

—Company-specific news extraction
—Advanced text summarization using Pegasus model
—Sentiment analysis with Hugging Face Model
—Topic extraction using LDA
—Comparative sentiment analysis
—Text-to-speech conversion in Hindi
—User-friendly Streamlit interface

Project Structure

Installation

1.Create a virtual environment:

bash

python -m venv myenv
# Windows
myenv\Scripts\activate

1.Install dependencies:

bash

   pip install -r requirements.txt

1.Run the application

streamlit run app.py

1.Usage

##Enter a company name and click "Analyze" to get:
-->News articles
-->Summaries
-->Sentiment analysis
-->Topic distribution
-->Comparative analysis
-->Audio output in Hindi
##Technical Details
-->Frontend: Streamlit
-->NLP Models:
-->Pegasus for summarization
-->FinBERT for sentiment analysis
-->LDA for topic modeling
-->Audio Processing: GTTS for text-to-speech
-->Backend: FastAPI
##Requirements
-->Python 3.8+
-->CUDA (optional for GPU acceleration)
-->Internet connection for model downloads

##License
-->MIT License

##Acknowledgments
-->Hugging Face for NLP models
-->Streamlit for web interface
-->NLTK for text processing