Emotion Detection Using Speech Analysis
Emotion Detection Using Speech Analysis
Jahnavi Patel
PG Department of Computer Applications JSS College of Arts, Commerce and Science (Autonomous), Ooty Road, Mysuru.
Mrs. Shwetha M R
Assistant Professor
PG Department of Computer Applications JSS College of Arts, Commerce and Science (Autonomous), Ooty Road, Mysuru.
ABSTRACT - Emotion detection using speech analysis has become an important research area in artificial intelligence and human-computer interaction. Human speech contains valuable emotional information that can be identified through variations in pitch, tone, intensity, rhythm, and other acoustic characteristics. This paper presents an intelligent emotion detection system that analyzes speech signals to recognize emotional states such as happiness, sadness, anger, fear, surprise, and neutrality. The proposed approach involves speech preprocessing, feature extraction, and classification using deep learning techniques. Important acoustic features are extracted from audio signals to capture emotional patterns and improve recognition performance. A convolutional neural network model is employed to learn complex relationships within speech data and accurately classify emotions. Experimental evaluation demonstrates that the proposed system achieves high recognition accuracy and effectively handles variations in speaker characteristics and recording conditions. The developed system can support a wide range of applications, including virtual assistants, healthcare monitoring, customer service analysis, educational systems, and intelligent communication platforms. The results indicate that speech-based emotion detection can significantly enhance machine understanding of human behavior and contribute to the development of more responsive and adaptive intelligent systems.
Index Terms - Artificial intelligence, deep learning, emotion detection, human-computer interaction, speech analysis.