President Botrick: An Analysis of Deep Learning-Based Conversational AI Models to Identify and Create Influential Political Speeches

Ada Tur, Julia Hirschberg

Abstract: This paper explores the defining qualities of language that are considered influential and charismatic in the context of political speech. Transformer-based models have shown to be efficient in analyzing contextual clues and generating coherent texts in a variety of domains. With limited research in the identification and exploration of the replication of persuasion in natural human language and generation of influential speech, we seek to analyze the aspects of public speech that are deemed persuasive and impactful, and generate text accordingly. We propose a two-part experiment: First, we train a BERT-based encoder to weigh segments of speech in order to predict its influence on an audience; second, we train a GPT-based decoder to use an established understanding of persuasion to generate new political speech. We show that, using these models, a speech can be created that mimics the natural language habits of prominent political figures.