# Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity

arXiv: https://arxiv.org/abs/2009.02685 · HTML: https://mlsanity.com/paper/2009.02685/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2020.

## Built on by (most cited first, 5 of 5)

- [Human Evaluation of Creative NLG Systems: An Interdisciplinary Survey on Recent Papers](https://mlsanity.com/paper/2108.00308/) (2021)
- [Dialectal Toxicity Detection: Evaluating LLM-as-a-Judge Consistency Across Language Varieties](https://mlsanity.com/paper/2411.10954/) (2024)
- [The Great Misalignment Problem in Human Evaluation of NLP Methods](https://mlsanity.com/paper/2104.05361/) (2021)
- [Finnish Dialect Identification: The Effect of Audio and Text](https://mlsanity.com/paper/2111.03800/) (2021)
- [The Current State of Finnish NLP](https://mlsanity.com/paper/2109.11326/) (2021)

## Abstract (arXiv)

We present a novel approach for adapting text written in standard Finnish to different dialects. We experiment with character level NMT models both by using a multi-dialectal and transfer learning approaches. The models are tested with over 20 different dialects. The results seem to favor transfer learning, although not strongly over the multi-dialectal approach. We study the influence dialectal adaptation has on perceived creativity of computer generated poetry. Our results suggest that the more the dialect deviates from the standard Finnish, the lower scores people tend to give on an existing evaluation metric. However, on a word association test, people associate creativity and originality more with dialect and fluency more with standard Finnish.