Automated Word Stress Detection in Russian

Autor:	Ponomareva, Maria, Milintsevich, Kirill, Chernyak, Ekaterina, Starostin, Anatoly
Rok vydání:	2019
Předmět:	Computer Science - Computation and Language
Zdroj:	Published in Proceedings of the First Workshop on Subword and Character Level Models in NLP, pages 31 35, Copenhagen, Denmark, September 7, 2017
Druh dokumentu:	Working Paper
Popis:	In this study we address the problem of automated word stress detection in Russian using character level models and no part-speech-taggers. We use a simple bidirectional RNN with LSTM nodes and achieve the accuracy of 90% or higher. We experiment with two training datasets and show that using the data from an annotated corpus is much more efficient than using a dictionary, since it allows us to take into account word frequencies and the morphological context of the word. Comment: SCLeM 2017
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1907.05757 Zobrazit plný text záznamu View this record from Arxiv