Fictional Language Generator

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Distributed Computing Prof. R. Wattenhofer Fictional Language Generator Sindarin, Klingon, Dothraki. These are some of the few fully developed fictional languages that you could actually learn to speak. There are some more \half-developed" languages (see \Artistic/Fictional languages" here), but it is a relatively short list. Imagine you want to make a movie or create a computer game, and you want some of your characters to speak a foreign/alien language to make it more believable for the au- dience (what kind of alien speaks English after all?!?). The problem is that creating a new language is a non-trivial task that re- quires deep knowledge of linguistics and a high amount of work. So in the end, it is either something for the gifted and passion- ate (e.g. Tolkien) or for the deep-pocketed (HBO with Game of Thrones, Hollywood with Avatar). This is where you come in! We want you to automatically create believable fictional languages. We already have some ideas on how to achieve this. We could for example use Deep Learning language models. We could also employ evolutionary algorithms to com- bine languages and then further process them with other techniques (real languages evolve as well, after all). We do not necessarily aim at creating perfect new languages, but something more believable than this is certainly doable. These are just some early ideas, but the area is completely open for exploration. If you are interested, do not hesitate to contact us so that we can have a chat! You will: Familiarize yourself with the necessary basics of linguistics and Natural Language Generation (NLG). Considerably improve your knowledge of Machine Learning techniques. Read papers on state-of-the-art generative learning algorithms. Implement different algorithms and evaluate them. Meet with your supervisors once a week to discuss progress and open questions. Requirements: Interest in languages and Machine Learning. Prior knowledge about Ma- chine learning is an advantage, but not a must. Contacts • Yuyi Wang: [email protected], ETZ G94 • Gino Brunner: [email protected], ETZ G63.

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