These include techniques for building effective language models for speech recognition when little or no multimodal training data is available, and techniques for robust multimodal understanding that draw on classification, machine translation, and sequence edit methods.
it attempts to classify the utterance and identifies substrings of the input as slotfiller values to construct a frame-like semantic representation.