You're making a presentation of a new neural network architecture for emotion recognition from audio and video. You're using data preprocessing, audio and video feature extraction, transfer learning, hyperparameter tuning, regularization, 3d cnn, group convolutions, residual learning, sliding window attention, relu activation functions, feature map classifier, batch optimization, evaluation metrics and anything else you need to put it together into a coherent architecture. For each key feature you use 1 to 3 slides with 2 to 3 paragraphs of text and formulas and equations. For each part of the network, you have to also explain how training it with backpropagation works with math behind it. Lay out the content of each slide. At the end of your presentation you explain how each part of your presentation fit together to build a coherent neural network architecture for solving the task.