Sentiment Analysis: Gauging Confidence and Engagement of Users

Project Description

The project aims to develop a system that analyzes users' voice tone and word choice to assess their confidence and engagement levels during interactions. The system will provide real-time insights and feedback, making it applicable in various domains such as customer service, education, and personal development. This project will leverage voice processing, NLP and machine learning models for sentiment analysis. Key activities will include: • Voice Processing: Ability to capture audio input with minimal background noise. • Implementation of algorithms for analyzing vocal characteristics (pitch, tone, volume). • Natural Language Processing (NLP): Text analysis capabilities to assess word choice, sentiment, and linguistic patterns. • Multilingual support for analyzing sentiment in various languages. • Real-Time Feedback Mechanism: User interface that displays engagement and confidence metrics immediately after user interactions. • Data Visualization: Dashboard for tracking sentiment trends over time, with graphical representations of engagement levels. • Integration Capabilities: Ability to integrate with existing applications (e.g., CRM systems, educational platforms).

Project Requirement File

Requester Details