Abstract: A method includes generating, using at least one processing device of an electronic device, a multilingual training corpus including labeled utterances in multiple languages including a first language and a second language. The multilingual training corpus includes at least one utterance that has been translated into the multiple languages. The method also includes fine-tuning, using the at least one processing device, a multilingual language model using the multilingual training corpus.

Abstract: In an embodiment of the present disclosure, a method of simultaneously identifying intent and slots in a voice assistant command includes tokenizing, into a plurality of tokens, a current utterance of a user of a device comprising the voice assistant command, prepending the plurality of tokens with a previous utterance and a separation token, obtaining, using a transformer-based machine learning model, one or more predictions for the voice assistant command from the prepended plurality of tokens, aligning, according to one or more constraints, the at least one of the flag prediction, the goal prediction, and the sub-goal prediction, providing, to the device, the identified intent and the identified slots based on the intent prediction and the aligned at least one of the flag prediction, the goal prediction, and the sub-goal prediction, causing the device to perform the voice assistant command according to the identified intent and the identified slots.