AI-Based Confidence Assessment System is a machine learning-driven application designed to automatically evaluate a person’s confidence level using speech signals. The system analyzes various acoustic features such as MFCC (Mel-Frequency Cepstral Coefficients), pitch, and energy extracted from audio recordings. These features are processed using supervised machine learning algorithms to classify the speaker’s confidence level into Low, Medium, or High categories. The project focuses on feature engineering, dataset creation, and model evaluation to ensure accurate and intelligent confidence prediction. By combining signal processing techniques with machine learning models such as Random Forest, the system demonstrates how AI can interpret behavioral patterns from speech. This project highlights the practical application of Artificial Intelligence and Machine Learning in behavioral analysis, communication assessment, and personal development systems.
Built With
- an
- and
- audio-based
- built-with-python
- classification
- confidence
- fastapi
- implement
- learning
- librosa
- machine
- scikit-learn
- to
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