Ilnar Salimzianov's Personal Site

Projects

Here are some of the projects I've worked on.

Trained a Kazakh automatic speech recognition model using the Coqui STT framework on the Yandex Data Spehere service.

A transition-based statistical dependency parser I wrote in Python for a class. The classifier of it is a simple perceptron, but you can plug in any other of your choice. Of course the parser is not as advanced as other parsers you might have used or heard of, but it can serve as a good starting point if you're implementing a dependency parser yourself or just want to see how a transition-based dependency parser works inside.

apertium-fitnesse

This was a proof-of-concept adaption of an acceptance testing framework called Fitnesse to a rule-based machine translation system called Apertium, with the aim of giving machine translation stakeholders an easy way to specify how translators and underlying NLP tools should behave. I have used it to guide the work of some of the Google Summer of Code students I've been mentoring.

bible.com scraper

A little Racket script for scraping Bible translations from the bible.com website. Bible translations are often used in natural language processing research, as it is the most translated text.

apertium-kaz

Extended with new stems, with support for some new affixes of Kazakh, with a Constraint Grammar including dependency parsing capabilities in the Universal Dependencies framework

finished updating of the UD_KTB teebank to the second version of Universal Dependencies annotation guidelines, along with an overall testing and error-checking of both the treebank and apertium-kaz

All of this is documented under https://taruen.com/apertiumpp/apertiumpp-kaz/ and http://taruen.com/apertium-kaz

If you use apertium-kaz in your research work, please cite the following paper: Jonathan North Washington, Ilnar Salimzyanov, and Francis M. Tyers. "Finite-state morphological transducers for three Kypchak languages." LREC. 2014.

apertium-kaz-tat