Update readme.md

readme.md

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-# Context-Aware Multimodal Assistant for Cognitive Load Management
+# Context-Aware Multimodal Assistant
 
-## What is this project about?
+## Overview
+This project builds a multimodal assistant that helps users manage cognitive load by detecting stress from voice recordings and facial images. Based on the stress level, it simplifies or rephrases user tasks or messages to make them easier to understand.
 
-This project builds an intelligent assistant designed to **help users manage tasks and information when they feel overwhelmed, stressed, or distracted**. It uses **voice input and facial images** to detect the user's stress level and adapts its responses accordingly. The assistant simplifies or rephrases the user's tasks or messages, making them easier to understand and act upon during moments of high cognitive load.
+## Features
+- Detects stress from voice and face inputs (placeholder logic, easy to replace).
+- Simplifies text input using the `facebook/bart-large-cnn` model from Hugging Face.
+- Interactive UI built with Gradio for easy testing and deployment.
 
----
+## How to Use
+1. Upload a voice recording (.wav) and a face image.
+2. Enter the task or message you want help with.
+3. The assistant detects your stress level and simplifies your input accordingly.
 
-## What does it do?
+## Technologies
+- Hugging Face Transformers (`facebook/bart-large-cnn`)
+- Gradio for the user interface
+- Torch and other libraries for processing
 
-- **Detects stress level** from user voice recordings and facial images.
-- **Simplifies or rephrases tasks and messages** based on the detected stress level.
-- Provides an easy way for users to input their task descriptions via voice, face image, and text.
-- Adapts the complexity and tone of the assistant’s responses to suit the user’s current mental state.
+## Future Work
+- Integrate real stress detection models for voice and facial expressions.
+- Add real-time input support.
+- Extend functionality for calendar and email summarization.
 
 ---
 
-## How does it help?
-
-- Reduces **cognitive overload** by presenting information in a simpler, clearer way.
-- Supports users in **staying focused and productive** during stressful or distracting moments.
-- Offers a **personalized interaction** by combining multimodal inputs — voice and vision — to better understand user context.
-- Makes digital communication and task management feel less daunting when the user is under pressure.
-
----
-
-## Key Features & Technologies Used
-
-- **Multimodal Inputs:**  
-  - **Speech (voice input):** Users upload voice recordings that the system analyzes for stress cues.  
-  - **Vision (facial images):** Webcam images are analyzed to detect facial expressions related to stress.
-
-- **Stress Detection Models:**  
-  - Placeholder dummy functions simulate stress detection for voice and face input (replaceable with real pretrained models).  
-
-- **Task Simplification:**  
-  - Uses the **T5-base** transformer model from Hugging Face for natural language simplification and paraphrasing.  
-  - Prompts guide the model to adapt outputs based on detected stress levels.
-
-- **User Interface:**  
-  - Built with **Gradio** for easy prototyping and interaction within a Google Colab notebook.  
-  - Planned deployment on **Hugging Face Spaces** with a simple UI for user-friendly access.
-
----
-
-## How to run the project
-
-1. Run the app locally or in Google Colab by uploading voice recordings and face images.
-2. Type your task or message into the input box.
-3. The assistant detects your stress level from voice and facial cues, then simplifies your message if needed.
-4. Get a clear, simplified response to help you manage your cognitive load.
-
----
-
-## Future Improvements
-
-- Replace dummy stress detection functions with real pretrained models for accurate voice and facial stress recognition.
-- Add real-time stress detection via webcam and live microphone.
-- Extend to handle calendar and email data for task summarization.
-- Personalize responses based on user history and preferences.
-- Add multilingual support for wider accessibility.
-
----
-
-## Acknowledgments
-
-This project leverages pretrained models and libraries from Hugging Face Transformers and Gradio, enabling accessible and powerful multimodal AI applications.
-
----
-
-Feel free to reach out if you want to collaborate or improve the project!
-
+Feel free to explore and contribute!