Publication at Faculty of Mathematics and Physics |
2019
Abstract
The deep learning methods of artificial neural networks have seen a significant uptake in recent years, and have succeeded in overcoming and advancing the success of auto-solving tasks in many fields. The field of computational linguistics and its application offshoot, natural language processing with classic tasks such as morphological tagging, dependency analysis, named entity recognition and machine translation are not exceptions.
This post provides an overview of recent advances in these tasks related to the Czech language and presents completely new results in the areas of morphological marking and recognition of named entities in Czech, along with detailed error analysis.