US 12,443,797 B1
Low-resource task-oriented semantic parsing via intrinsic modeling for assistant systems
Shrey Desai, Palo Alto, CA (US); Akshat Shrivastava, Redmond, WA (US); Alexander Kolmykov-Zotov, Sammamish, WA (US); and Ahmed Aly, Kenmore, WA (US)
Assigned to Meta Platforms, Inc., Menlo Park, CA (US)
Filed by Meta Platforms, Inc., Menlo Park, CA (US)
Filed on Dec. 6, 2021, as Appl. No. 17/543,178.
Int. Cl. G06F 40/295 (2020.01); G06F 40/205 (2020.01); G10L 15/18 (2013.01)
CPC G06F 40/295 (2020.01) [G06F 40/205 (2020.01); G10L 15/1822 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving one or more training utterances associated with a domain, the domain being associated with
one or more ontology labels that comprise one or more of an intent or a slot;
identifying, for each ontology label, a respective index and a respective span;
obtaining an inventory for the domain, wherein the inventory comprises at least the respective index and the respective span, wherein the respective span comprises a respective descriptive label, and wherein the respective descriptive label comprises a natural-language description of the intent or the slot associated with the one or more ontology labels;
obtaining, based on the one or more training utterances and the inventory by a natural language understanding (NLU) model, a structural representation of a respective training utterance, wherein the structural representation is generated based on a comparison between the respective training utterance and the inventory; and
obtaining an updated NLU model based on the structural representation and the respective training utterance.