id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_jqo6bqehefaodeuuboo6oybjq4	Jayant Krishnamurthy	Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World	2013	14	.pdf	application/pdf	7912	814	61	Perception (LSP), a model for grounded language acquisition that learns to map natural language statements to their referents in to identify (1) the objects in its environment corresponding to "blue mug" and "table," and (2) the objects which participate in the spatial relation denoted mapping from natural language queries to sets of objects in a real-world environment. natural language query, LSP produces a semantic parse, logical knowledge base, grounding and denotation mug." Given these inputs, LSP produces (1) a logical knowledge base describing objects and relationships in the environment and (2) a semantic parse of The first contribution is LSP, which is more expressive than previous models, representing both one-argument categories and two-argument relations over sets of objects in the environment. is a weakly supervised training procedure that estimates LSP's parameters without annotated semantic This paper introduces Logical Semantics with Perception (LSP), a model for mapping natural language statements to their referents in a physical environment.	./cache/work_jqo6bqehefaodeuuboo6oybjq4.pdf	./txt/work_jqo6bqehefaodeuuboo6oybjq4.txt