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I survey some recent applications-oriented NL generation systems, and claim that despite very different theoretical backgrounds, these systems have a remarkably similar architecture in terms of the modules they divide the generation process into, the computations these modules perform, and the way the modules interact with each other. I also compare this 'consensus architecture' among applied NLG systems with psycholinguistic knowledge about how humans speak, and argue that at least some aspects of the consensus architecture seem to be in agreement with what is known about human language production, despite the fact that psycholinguistic plausibility was not in general a goal of the developers of the surveyed systems.
Ehud Reiter (Sat,) studied this question.
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