English-Kazakh Parallel Corpus For Statistical Machine Translation

2014

Closed access Metadata (CSL-JSON)
DOI 10.5121/ijnlc.2014.3306
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This paper presents problems and solutions in developing English-Kazakh parallel corpus at the School of Mechanics and Mathematics of the al-Farabi Kazakh National University.The research project included constructing a 1,000,000-word English-Kazakh parallel corpus of legal texts, developing an English-Kazakh translation memory of legal texts from the corpus and building a statistical machine translation system.The project aims at collecting more than ten million words.The paper further elaborates on the procedures followed to construct the corpus and develop the other products of the research project.Methods used for collecting data and the results are discussed, errors during the process of collecting data and how to handle these errors will be described.