I am trying to train a LSTM model to predict speech veracity using video as input. I have a dataset per video and each dataset contains its own timestamp. I have been trying to prepare each dataset as a time series for model training. I have tried combining all the datasets into a single one, however i am not sure if that is the right procedure due to the videos not being ordered in the final dataset as a time series should be. I have also tried fitting the model with one dataset at a time.
This is how the video datasets look like
This is how the dataset looks after some preprocessing
What is the best way to apply the multiple datasets to a LSTM model?