Romanian Part of Speech Tagging using LSTM Networks

Beata Lorincz, Maria Nutu, Adriana Stan
2019 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)  
In this paper we present LSTM based neural network architectures for determining the part of speech (POS) tags for Romanian words. LSTM networks combined with fullyconnected output layers are used for predicting the root POS, and sequence-to-sequence models composed of LSTM encoders and decoders are evaluated for predicting the extended MSD and CTAG tags. The highest accuracy achieved for the root POS is 99.18% and for the extended tags is 98.25%. This method proves to be efficient for the
more » ... icient for the proposed task and has the advantage of being language independent, as no expert linguistic knowledge is used in the input features.
doi:10.1109/iccp48234.2019.8959730 dblp:conf/iccp2/LorinczNS19 fatcat:ogfemglfgzdidgywuaqvxnrkai