Evaluating Speech Emotion Recognition through the lens of CNN & LSTM Deep Learning Models

Speech Emotion Recognition (SER) is a fascinating area of research in machine learning. Researchers have been exploring different techniques to improve this field including using deep learning models, feature extraction methods and transfer strategies to improve the accuracy and robustness of SER models. The advancements in SER not only contribute to the field of artificial intelligence but also have the potential to enhance our understanding of human emotions and improve communication between humans and machines.