We use the method of BIBREF5 to train neural sequence-to-sequence Spanish-English ST models. Obtaining gold topic labels for our data would require substantial manual annotation, so we instead use the human translations from the 1K (train20h) training set utterances to train the NMF topic model with scikit-learn BIBREF14 
 Question: What is the architecture of the model?
BIBREF5 to train neural sequence-to-sequence NMF topic model with scikit-learn BIBREF14