How can a data stream for a RNN (LSTM) be handled, when the stream contains data sets belonging to different prediction classes?
Training phase: I have trained a LSTM to predict a class out of a sequence of Letters. For the training phase I used a fixed data array where the beginning an the ending of a sequence belonged to a class. Of course there is a little noise but the whole data set was labled with a class. E.g:
Seq. is Class ABC is One CBA is Two ABD is Three
The network predicts well when it sees a static data array.
Problem in Prediction Phase: During prediction the LSTM will receive a data stream where there is a sequence off arrays but there is no delimiter. The data set can not be distinguished or separated. I am not sure how it would perform when I have a data stream for different classes like ABCABCCBAABD.
I guess in speech recognition one must face similiar problems.