Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning

Benchmark Model Rank Results
emotion-recognition-on-ravdessLogistic Regression on posteriors of the CNN-14&biLSTM-GuidedSTAccuracy: 80.08%
facial-emotion-recognition-on-ravdessGuided-ST and bi-LSTM with attentionAccuracy: 57.08%
speech-emotion-recognition-on-ravdessAlexNet (FineTuning)Accuracy: 61.67%
speech-emotion-recognition-on-ravdessCNN-14 (Fine-Tuning)Accuracy: 76.58%