# Extending the Vocabulary of Fictional Languages using Neural Networks

arXiv: https://arxiv.org/abs/2201.07288 · HTML: https://mlsanity.com/paper/2201.07288/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 29 references that are in the map.
- First posted on arXiv 18 Jan 2022.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation](https://mlsanity.com/paper/1406.1078/) (2014)
- [Sequence to Sequence Learning with Neural Networks](https://mlsanity.com/paper/1409.3215/) (2014)
- [Character-level Convolutional Networks for Text Classification](https://mlsanity.com/paper/1509.01626/) (2015)
- [Toward Controlled Generation of Text](https://mlsanity.com/paper/1703.00955/) (2017)
- [Style Transfer from Non-Parallel Text by Cross-Alignment](https://mlsanity.com/paper/1705.09655/) (2017)
- [Coupled Generative Adversarial Networks](https://mlsanity.com/paper/1606.07536/) (2016)
- [Deep Photo Style Transfer](https://mlsanity.com/paper/1703.07511/) (2017)
- [Learning to Generate Reviews and Discovering Sentiment](https://mlsanity.com/paper/1704.01444/) (2017)
- [Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Models](https://mlsanity.com/paper/1707.01161/) (2017)
- [Domain Adaptive Text Style Transfer](https://mlsanity.com/paper/1908.09395/) (2019)
- [Evaluating prose style transfer with the Bible](https://mlsanity.com/paper/1711.04731/) (2017)
- [Learning Sentiment Memories for Sentiment Modification without Parallel Data](https://mlsanity.com/paper/1808.07311/) (2018)
- [Language Style Transfer from Sentences with Arbitrary Unknown Styles](https://mlsanity.com/paper/1808.04071/) (2018)

## Built on by (most cited first, 1 of 1)

- [A Network Analysis Approach to Conlang Research Literature](https://mlsanity.com/paper/2407.15370/) (2024)

## Abstract (arXiv)

Fictional languages have become increasingly popular over the recent years appearing in novels, movies, TV shows, comics, and video games. While some of these fictional languages have a complete vocabulary, most do not. We propose a deep learning solution to the problem. Using style transfer and machine translation tools, we generate new words for a given target fictional language, while maintaining the style of its creator, hence extending this language vocabulary.