An Unsupervised Dynamic Bayesian Network Approach to Measuring Speech Style Accommodation
نویسندگان
چکیده
Speech style accommodation refers to shifts in style that are used to achieve strategic goals within interactions. Models of stylistic shift that focus on specific features are limited in terms of the contexts to which they can be applied if the goal of the analysis is to model socially motivated speech style accommodation. In this paper, we present an unsupervised Dynamic Bayesian Model that allows us to model stylistic style accommodation in a way that is agnostic to which specific speech style features will shift in a way that resembles socially motivated stylistic variation. This greatly expands the applicability of the model across contexts. Our hypothesis is that stylistic shifts that occur as a result of social processes are likely to display some consistency over time, and if we leverage this insight in our model,we will achieve a model that better captures inherent structure within speech.
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