@InProceedings{ponomareva-EtAl:2017:SCLeM,
  author    = {Ponomareva, Maria  and  Milintsevich, Kirill  and  Chernyak, Ekaterina  and  Starostin, Anatoly},
  title     = {Automated Word Stress Detection in Russian},
  booktitle = {Proceedings of the First Workshop on Subword and Character Level Models in NLP},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {31--35},
  abstract  = {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 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 only a dictionary,
	since it allows to retain the context of the word and its morphological
	features.},
  url       = {http://www.aclweb.org/anthology/W17-4104}
}