Prediction of stress of Slovenian words with machine learning methods

Luka Krsnik (2017) Prediction of stress of Slovenian words with machine learning methods. MSc thesis.

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Abstract

There is no simple algorithm for stress assignment of Slovene words. Speakers of Slovene are usually taught accents together with words. Machine learning algorithms give positive results on this problem, therefore we tried deep neural networks. We tested different architectures, data presentations and an ensemble of networks. We achieved the best results using the ensemble method, which correctly predicted 87,62 % of tested words. Our neural network approach improved results of other machine learning methods and proved to be successful in stress assignment.

Item Type:

Thesis (MSc thesis)

Keywords:

artificial inteligence, data mining, machine learning, deep neural networks, natural language processing, accentuation

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
izr. prof. dr. Marko Robnik Šikonja	276	Mentor
doc. dr. Tomaž Šef		Comentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537581251)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

3978

Date Deposited:

26 Sep 2017 14:39

Last Modified:

10 Oct 2017 10:50

URI:

http://eprints.fri.uni-lj.si/id/eprint/3978

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