readme.md

News Sentiment Analysis & Hindi Text-to-Speech (TTS) Web Application

Objective

This project is a web-based application that:

• Extracts key details from multiple news articles about a user-provided company
• Performs sentiment analysis
• Conducts comparative sentiment analysis
• Generates a Hindi Text-to-Speech (TTS) audio report
• Provides a user-friendly interface for interaction

The tool allows users to input a company name and receive a structured sentiment report along with audio output.

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Features

1. News Extraction: Scrapes and displays the title, summary, and metadata from at least 10 unique news articles (non-JavaScript pages) using BeautifulSoup (bs4).
2. Sentiment Analysis: Determines the sentiment (positive, negative, neutral) of each article.
3. Comparative Analysis: Compares sentiment across articles to visualize sentiment distribution.
4. Hindi TTS Generation: Converts summarized insights into Hindi audio using an open-source TTS model.
5. User Interface: Simple web UI built with Streamlit or Gradio.
6. API Communication: Frontend and backend communicate via REST APIs.
7. Deployment: Live deployment on Hugging Face Spaces.
8. Documentation: Complete setup and usage guide.

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Project Setup

Clone the Repository

git clone https://github.com/yourusername/news-sentiment-tts.git
cd news-sentiment-tts

Create Virtual Environment & Install Dependencies

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

Run the Application Locally

streamlit run app.py

python api.py

or

python app.py  # If using Gradio

Deployment

The app is deployed on Hugging Face Spaces:

https://huggingface.co/spaces/yourusername/news-sentiment-tts

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Model Details

Task	Model Used	Description
Summarization	transformers.pipeline('summarization')	Hugging Face pre-trained model for article summary generation
Sentiment Analysis	transformers.pipeline('sentiment-analysis')	Classifies article sentiment into Positive/Negative/Neutral
Text-to-Speech	Coqui TTS / indic-tts	Open-source TTS model to generate Hindi speech from text

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API Development & Usage

Backend APIs:

• Endpoint: /analyze_news
  • Method: POST
  • Input: {"company": "Company Name"}
  • Output: List of news articles with metadata

Testing with Postman:

1. Set API base URL as http://localhost:8000/
2. Select appropriate endpoints and POST body
3. Test responses for JSON or audio file streaming

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Third-Party API Usage

API/Library	Purpose
News scraping	BeautifulSoup (no external news APIs used)
Hugging Face models	Sentiment analysis & summarization
gtts	Hindi Text-to-Speech generation

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Assumptions & Limitations

• Scraping Limitations: Only static, non-JS websites are scraped due to BeautifulSoup limitations. Also newsorg pi is also used.
• Article Count: A minimum of 10 articles is targeted, but the count may vary based on search results.
• Language Support: Sentiment analysis is primarily in English, TTS is specifically Hindi.
• Deployment: Optimized for Hugging Face Spaces; heavy TTS models may experience latency. Due to flask being used hugging face is not able to run two files at a time

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Dependencies

beautifulsoup4
requests
transformers
torch
streamlit
gtts
scikit-learn

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