Physics

Interrogative

Human–computer interaction

World Wide Web

Visual arts

Philosophy

Artificial intelligence

Dialog box

Dialog system

Natural language processing

Scale (ratio)

Computer science

Linguistics

Quantum mechanics

Persuasion

Generative grammar

Entertainment

In this work, we perform the first large-scale analysis of discourse in media dialog and its impact on generative modeling of dialog turns, with a focus on interrogative patterns and use of external knowledge. Discourse analysis can help us understand modes of persuasion, entertainment, and information elicitation in such settings, but has been limited to manual review of small corpora. We introduce **Interview**—a large-scale (105K conversations) media dialog dataset collected from news interview transcripts—which allows us to investigate such patterns at scale. We present a dialog model that leverages external knowledge as well as dialog acts via auxiliary losses and demonstrate that our model quantitatively and qualitatively outperforms strong discourse-agnostic baselines for dialog modeling—generating more specific and topical responses in interview-style conversations.

Interview: Large-scale Modeling of Media Dialog with Discourse Patterns and Knowledge Grounding