Project

AIGRE: Natural Language Interface that Accommodates Vague and Ambiguous Input

None

A major problem for natural language interfaces is their inability to handle text whose meaning depends in part on context. If a user asks his car radio to play "a fast song," or his calendar to schedule "a short meeting," the interpreter would have to accommodate vagueness and ambiguity to figure out what he meant based on what he said. For it to understand what songs or events the speaker intended, it must make decisions that depend on assumed common knowledge about the world and language. Our research presents two approaches for reducing uncertainty in natural language interfaces, by modeling interpretation as a plan recognition problem.

A major problem for natural language interfaces is their inability to handle text whose meaning depends in part on context. If a user asks his car radio to play "a fast song," or his calendar to schedule "a short meeting," the interpreter would have to accommodate vagueness and ambiguity to figure out what he meant based on what he said. For it to understand what songs or events the speaker intended, it must make decisions that depend on assumed common knowledge about the world and language. Our research presents two approaches for reducing uncertainty in natural language interfaces, by modeling interpretation as a plan recognition problem.