Attention, intentions, and the structure of discourse
Computational Linguistics
The society of mind
Making computers laugh: investigations in automatic humor recognition
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
| Hi-index | 0.00 |
Many verbal jokes, like garden path sentences, pose difficulties to models of discourse since the initially primed interpretation needs to be discarded and a new one created based on subsequent statements. The effect of the joke depends on the fact that the second (correct) interpretation was not visible earlier. Existing models of discourse semantics in principle generate all interpretations of discourse fragments and carry these until contradicted, and thus the dissonance criteria in humour cannot be met. Computationally, maintaining all possible worlds in a discourse is very inefficient, thus computing only the maximum-likelihood interpretation seems to be a more efficient choice on average. In this work we outline a probabilistic lexicon based lexical semantics approach which seems to be a reasonable construct for discourse in general and use some examples from humour to demonstrate its working.