Intelligent In-Car Emotion Regulation Interaction System Based on Speech Emotion Recognition

With driving emerging as a common mode of transportation, the automotive industry has increasingly prioritized driving safety and experience. A substantial body of research focused on driving safety and the overall travel experience has underscored the pivotal role of emotions. In this article, we introduce an innovative in-car emotion recognition and interaction system, carefully crafted to intelligently respond to the emotional states of drivers. This system captures real-time emotional data through its user input layer and seamlessly integrates it into the technological architecture layer, residing within the vehicle's CPU. Leveraging cutting-edge deep learning models for emotion recognition, the system's outcomes trigger tailored emotion regulation strategies within the interaction feedback layer. Notably, our study introduces a groundbreaking speech fusion feature, MFCCs+, meticulously crafted for driving contexts. Furthermore, we have optimized the driving speech emotion recognition model using 1D-CNN, resulting in a remarkable 10% improvement in recognition accuracy. Subsequent validation experiments affirm the system's effectiveness in enhancing driving safety. In conclusion, the integration of emotion-based interaction solutions holds immense potential for elevating both driving safety and the overall travel experience within intelligent driving scenarios. This innovation promises to shape the future landscape of automotive travel, offering a safer and more enjoyable journey for all.