Author(s)

Ali Pourmohammad ¹, Mensur Gulami ², Javid Mahmudov ², Yusif Aliyev ², Rovshan Akberov ²

Affiliation(s)

¹ Process Automation Engineering Department Baku Higher Oil School Baku, Azerbaijan
² Department of Computer Science, Khazar University, Baku, Azerbaijan

Corresponding Author

Ali Pourmohammad

ABSTRACT

Azeri (Azerbaijani) language is one of the more than 50 Turkic languages which it is a little studied language in terms of using the modern signal processing algorithms. This paper tackles the problem of Hidden Markov Models (HMMs) based next word prediction for this language based on Natural Language Processing (NLP) principles using Python high-level programming language. The software is included a small Azeri vocabulary database, the various Python libraries, a HMM model and a Web based interface. In this research, the database was constructed by a predictor parser which it was implemented for the first time for Azeri language. The database was concluded by the most general Azeri language words to introduce HMMs based generated word pairs. The Model was trained by 90% of the database, hence, predicting the next 5 words on the test data resulted 54% accuracy. 

KEYWORDS

Azeri (Azerbaijani) Language; Next Word Predictor; Hidden Markov Model (HMM), Natural Language Processing (NLP)

CITE THIS PAPER

Ali Pourmohammad, Mensur Gulami, Javid Mahmudov, Yusif Aliyev, Rovshan Akberov, The First Azeri (Azerbaijani) Language Next Word Predictor. Information Systems and Signal Processing Journal (2020) 5: 1-4. DOI: http://dx.doi.org/10.23977/isspj.2020.51001.

REFERENCES

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