New PDF release: A Computational Model of Natural Language Communication:

By Roland R. Hausser

The excellent of utilizing human language to regulate machines calls for a realistic concept of typical language conversation that incorporates grammatical research of language indicators, plus a version of the cognitive agent, with interfaces for attractiveness and motion, an inner database, and an set of rules for interpreting content material out and in. This e-book bargains a practical framework for theoretical research of ordinary language conversation and for useful purposes of typical language processing.

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Extra resources for A Computational Model of Natural Language Communication: Interpretation, Inference, and Production in Database Semantics

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Meaning1 is the literal meaning of the sign; meaning2 is the speaker meaning of an utterance in which the sign’s meaning1 is used. Even in the hearer mode, meaning2 is called the “speaker meaning” because communication is successful only if the hearer uses the sign’s meaning1 to refer to the same objects or events as the speaker. A sign can only be used successfully if the context of interpretation has been determined (and delimited) correctly. 2 S ECOND PRINCIPLE OF PRAGMATICS ( POP -2) A sign’s STAR determines the entry context of production and interpretation in the contextual databases of the speaker and the hearer.

The data structure supporting the algorithm is a classic network database (cf. Elmasri and Navathe 1989), called Word Bank; it stores flat (nonrecursive) feature structures, called proplets, which are structurally equivalent to the records of classic databases. 1 Proplets for Coding Propositional Content A feature structure is defined as a set of features. 1 In proplets, the attributes are displayed in a predefined standard order (for better readability and improved computational efficiency). 1 C ONTEXT PROPLETS REPRESENTING dog barks.

Thus, a VNN navigation is realized here as a surface with the word order n fv n p. This method of production can be used to realize not only a subject–verb–object surface (SVO)12 as in the above example, but also an SOV and (trivially) a VSO surface (cf. Appendix A). 3. The operations of the three LA-grammars partially13 determine the possible states of the artificial agent: When LA-hear is active, the agent is in the hearer mode; when LA-think is active, the agent is in the think mode; when LA-think and LA-speak are active, the agent is in the speaker mode.

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A Computational Model of Natural Language Communication: Interpretation, Inference, and Production in Database Semantics by Roland R. Hausser

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