Methods and Systems for Intent Detection and Slot Filling in Spoken Dialogue Systems

A system for spoken language understanding (SLU) comprising:

• a memory configured to store:
• a recurrent neural network (RNN) encoder;
• a first RNN decoder;
• a second RNN decoder;
• and
• a third RNN decoder;
• an input device;
• and
• a processor operatively connected to the memory and the input device, the processor being configured to:
• receive a plurality of words in a text phrase from the input device;
• generate a first encoded representation of the plurality of words based on an output of the RNN encoder using the plurality of words as inputs to the RNN encoder;
• generate an intent label corresponding to the plurality of words based on an output of the first RNN decoder using the first encoded representation as input to the first RNN decoder;
• generate a corrected plurality of words based on an output of the second RNN decoder using the first encoded representation and the intent label as inputs to the second RNN decoder, the corrected plurality of words including at least one word that is different than one of the plurality of words in the text phrase;
• generate a second encoded representation corresponding to the plurality of corrected words based on another output of the RNN encoder using the plurality of corrected words as inputs to the RNN encoder;
• and
• generate a machine-readable dialogue phrase that includes at least one word in the plurality of corrected words assigned to at least one slot in the machine-readable dialogue phrase based on an output of the third RNN decoder using the second encoded representation of the plurality of corrected words and the intent label as inputs to the third RNN decoder.