Slot filling in spoken language comprehension with a combination of pointer and attention

摘要

A method for slot filling in an automatic voice speech understanding (SLU) system includes receiving words in a textual expression, generating encrypted output, and attentional weights using a Recurrent Neural Network (RNN). An encoder having an attention mechanism, generating first and second probability distributions of slot words in an extended slot vocabulary database using an RNN decoder, respectively, for a time step, generating a combined probability distribution based on the first and second second probability distribution and identifying a slot word corresponding to a word in the extended slot vocabulary database having a highest probability value in the combined probability distribution for the time step.