Year: 2025
Type: article
Abstract: - In recent times, recognizing human emotions accurately has become crucial for enhancing humancomputer interaction. Speech Emotion Recognition (SER) enables systems to interpret emotional states from speech signals, improving applications such as virtual assistants, mental health monitoring, and affective computing. However, accurately classifying emotions remains a challenge due to the complexity of speech variations. In this paper, we propose a hybrid approach that integrates traditional machine learning techniques with deep learning models to improve emotion classification.
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4411468926