Ilnar Salimzyanov


2018

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Rule-based machine translation from Kazakh to Turkish
Sevilay Bayatli | Sefer Kurnaz | Ilnar Salimzyanov | Jonathan Washington | Francis M. Tyers
Proceedings of the 21st Annual Conference of the European Association for Machine Translation

This paper presents a shallow-transfer machine translation (MT) system for translating from Kazakh to Turkish. Background on the differences between the languages is presented, followed by how the system was designed to handle some of these differences. The system is based on the Apertium free/open-source machine translation platform. The structure of the system and how it works is described, along with an evaluation against two competing systems. Linguistic components were developed, including a Kazakh-Turkish bilingual dictionary, Constraint Grammar disambiguation rules, lexical selection rules, and structural transfer rules. With many known issues yet to be addressed, our RBMT system has reached performance comparable to publicly-available corpus-based MT systems between the languages.

2014

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Finite-state morphological transducers for three Kypchak languages
Jonathan Washington | Ilnar Salimzyanov | Francis Tyers
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper describes the development of free/open-source finite-state morphological transducers for three Turkic languages―Kazakh, Tatar, and Kumyk―representing one language from each of the three sub-branches of the Kypchak branch of Turkic. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST). This paper describes how the development of a transducer for each subsequent closely-related language took less development time. An evaluation is presented which shows that the transducers all have a reasonable coverage―around 90%―on freely available corpora of the languages, and high precision over a manually verified test set.

2013

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A Free/Open-source Kazakh-Tatar Machine Translation System
Ilnar Salimzyanov | Jonathan Washington | Francis Tyers
Proceedings of Machine Translation Summit XIV: Papers