Our model separates the responsibilities for utterance representation and domain classification between the shared encoder and the domain-specific classifiers.
the shared encoder needs to be retrained only if it cannot encode an utterance well (e.g., a new domain introduces completely new words) and the existing domain classifiers need to be retrained only when the shared encoder changes.