This application integrates three powerful features: news summarization, sentiment analysis, and text-to-speech (TTS) generation. Designed to help users access concise summaries of news articles, analyze sentiment, and listen to the summary in audio format, this application is perfect for enhancing user engagement with real-time news content. Features: 1.News Summarization: Utilizes the state-of-the-art BART model for automatic summarization of articles, providing concise yet informative summaries. 2.Sentiment Analysis: Analyzes the sentiment of the news summary using the VADER Sentiment Analysis model, categorizing it as Positive, Negative, or Neutral. 3. Text-to-Speech (TTS): Converts the generated summary into Hindi speech using the gTTS (Google Text-to-Speech) API for seamless auditory content delivery. Technologies Used: - Python: Core language for the application. - Hugging Face Transformers: For news summarization using the pre-trained BART model. - VADER Sentiment Analysis: For text sentiment evaluation. - gTTS: For converting text to speech. - Streamlit: Web interface to interact with the application locally. - NewsAPI: For fetching real-time news articles based on a specified company name.