Sentence examples for automatic discourse from inspiring English sources
This result shows usefulness of pauses to distinguish between different situational context and cognitive task and therefore it could find application for automatic discourse analysis and conversation modeling purposes.
The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure.
Here we present the means to facilitate automatic access to the scientific discourse of articles by automating the recognition of 11 categories at the sentence level, which we call Core Scientific Concepts (CoreSCs).
Based on our previous work on automatic extraction of interpretable topics from online discourse (Zhang et al. 2012), we define a hot topic as HT = {focal: facet 1, facet 2, …, facet n }, where HT represents a hot topic.
Discourse markers, far from being opaque, automatic, or zombie-like, show that the speaker has "a desire to share or rephrase opinions to recipients".
The discourse feature extraction relies on the same automatic speech recognition module as described in the lexical features (Lexical features).
The automatic recognition of dialogue act is a task of crucial importance for the processing of natural language dialogue at discourse level.
A gun silences discourse.
Civil discourse = bad ratings.
