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Wednesday, January 20, 2016

AI And Political Speech Writing

How an AI Algorithm Learned to Write Political Speeches

Political speeches are often written for politicians by trusted aides and confidantes. Could an AI algorithm do as well?

MIT Technology Review | January 19, 2016

When it comes to political speeches, great ones are few and far between. But ordinary political speeches, those given in U.S. congressional floor debates, for example, are numerous.
They are also remarkably similar. These speeches tend to follow a standard format, repeat similar arguments, and even use the same phrases to indicate a particular political affiliation or opinion. It’s almost as if there is some kind of algorithm that determines their content.
That raises an interesting question. Is it possible for a machine to write these kinds of political speeches automatically?


<more at >; related links: (valentin012/conspeech) and (Political Speech Generation. Valentin Kassarnig. arXiv:1601.03313 [cs.CL]. Submitted January 13, 2016. [Summary: 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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