Voice to text fillable form 2025

The document presents a multi-modal emotion recognition system that integrates speech and text analysis to identify emotional states. It details the extraction of acoustic features from speech using Principal Component Analysis (PCA) and Support Vector Machines (SVM) for classification, alongside a textual analysis that defines emotional keywords and their intensity based on a corpus. The system aims to classify emotions into six categories: happiness, sadness, anger, fear, surprise, and disgust. Experimental results demonstrate that the combined approach outperforms individual methods in recognizing emotions, highlighting the effectiveness of integrating both speech and text inputs.