Political Speech Generation

Valentin Kassarnig
1/13/2016
cs.CL

Official code: valentin012/conspeech (346 stars, last commit 2016-01-31).

Abstract

In this report we present a system that can generate political speeches for a desired political party. Furthermore, the system allows to specify whether a speech should hold a supportive or opposing opinion. The system relies on a combination of several state-of-the-art NLP methods which are discussed in this report. These include n-grams, Justeson & Katz POS tag filter, recurrent neural networks, and latent Dirichlet allocation. Sequences of words are generated based on probabilities obtained from two underlying models: A language model takes care of the grammatical correctness while a topic model aims for textual consistency. Both models were trained on the Convote dataset which contains transcripts from US congressional floor debates. Furthermore, we present a manual and an automated approach to evaluate the quality of generated speeches. In an experimental evaluation generated speeches have shown very high quality in terms of grammatical correctness and sentence transitions.

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Code Implementations(1)

valentin012/conspeechOfficial100%

Political Speech Generator

34664Python, OpenEdge ABLJan 13, 201610 years ago

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Cite this paper

@article{kassarnig2016political,
  title  = {Political Speech Generation},
  author = {Valentin Kassarnig},
  year   = {2016},
  eprint = {1601.03313},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1601.03313}
}

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