Skip to content
DSML.KZ
Publications

Talk · International Conference on Electronics, Computer and Computation · November 25, 2021

Part-of-speech tagging of Kazakh text via LSTM network with a bidirectional modifier

Azamat Serek, Ainur Issabek, Adil Akhmetov, Alisher Sattarbek

Azamat Serek
Open via DOI

Abstract

In this paper, part-of-speech tagging on Kazakh text has been implemented using an LSTM neural network with a bidirectional modifier. A quite simple and fast tagger has been built, tested and evaluated on the self-collected dataset of Kazakh sentences with an accuracy of 94 %. There was addressed basically the problem of tagging having a small number of training samples (around 100 Kazakh sentences). It has been shown that quite good accuracy can be achieved in this situation.

Natural Language Processing TechniquesTopic ModelingSentiment Analysis and Opinion Miningpart-of-speech taggingKazakh languagebidirectional LSTM

More by Azamat Serek