Pragmatics and natural language generation
Artificial Intelligence
Using Grice's maxim of quantity to select the content of plan descriptions
Artificial Intelligence
ELIZA—a computer program for the study of natural language communication between man and machine
Communications of the ACM
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Automatic generation of textual summaries from neonatal intensive care data
Artificial Intelligence
Pictorial representations of routes: chunking route segments during comprehension
Spatial cognition III
Structural salience of landmarks for route directions
COSIT'05 Proceedings of the 2005 international conference on Spatial Information Theory
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Some of the systems used in natural language generation (NLG), a branch of applied computational linguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams' account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence embedded in their datasets enhances these speech capacities. Although there is an open question about who is ultimately responsible for their speech, if anybody, we can settle this question by using the notion of proxy speech, in which responsibility for artificial speech acts is assigned legally or conventionally to an entity separate from the speech actant.