|dc.contributor.advisor||Moore, Johanna D.||
|dc.description.abstract||This thesis explores approaches to modelling individual differences in language use.
The differences under consideration fall into two broad categories: Variation of the personality
projected through language, and modelling of language alignment behaviour
between dialogue partners. In a way, these two aspects oppose each other – language
related to varying personalities should be recognisably different, while aligning speakers
agree on common language during a dialogue.
The central hypothesis is that such variation can be captured and produced with
restricted computational means. Results from research on personality psychology and
psycholinguistics are transformed into a series of lexically-based Affective Language
Production Models (ALPMs) which are parameterisable for personality and alignment.
The models are then explored by varying the parameters and observing the language
ALPM-1 and ALPM-2 re-generate dialogues from existing utterances which are
ranked and filtered according to manually selected linguistic and psycholinguistic features
that were found to be related to personality. ALPM-3 is based on true overgeneration
of paraphrases from semantic representations using the OPENCCG framework
for Combinatory Categorial Grammar (CCG), in combination with corpus-based ranking
and filtering by way of n-gram language models. Personality effects are achieved
through language models built from the language of speakers of known personality. In
ALPM-4, alignment is captured via a cache language model that remembers the previous
utterance and thus influences the choice of the next. This model provides a unified
treatment of personality and alignment processes in dialogue.
In order to evaluate the ALPMs, dialogues between computer characters were generated
and presented to human judges who were asked to assess the characters’ personality.
In further internal simulations, cache language models were used to reproduce
results of psycholinguistic priming studies. The experiments showed that the models
are capable of producing natural language dialogue which exhibits human-like personality
and alignment effects.||en
|dc.publisher||The University of Edinburgh||en
|dc.subject||natural language processing||en
|dc.subject||natural language generation||en
|dc.title||Personality and alignment processes in dialogue: towards a lexically-based unified model||en
|dc.type||Thesis or Dissertation||en
|dc.type.qualificationname||PhD Doctor of Philosophy||en