Publikation
Qualitative: Open source Python tool for Quality Estimation over multiple Machine Translation outputs
Eleftherios Avramidis; Lukas Poustka; Sven Schmeier
In: Jan Hajič (Hrsg.). The Prague Bulletin of Mathematical Linguistics (PBML), Vol. 102, Pages 5-16, Charles University in Prague, Prague, Czech Republic, 10/2014.
Zusammenfassung
“Qualitative” is a python toolkit for ranking and selection of sentence-level output by different MT systems using Quality Estimation. The toolkit implements a basic pipeline for annotating the given sentences with black-box features. Consequently, it applies a machine learning mechanism in order to rank data based on models pre-trained on human preferences. The preprocessing pipeline includes support for language models, PCFG parsing, language checking tools and various other pre-processors and feature generators. The code follows the principles of object-oriented programming to allow modularity and extensibility. The tool can operate by processing both batch-files and single sentences. An XML-RPC interface is provided for hooking up with web-services and a graphical animated web-based interface demonstrates its potential on-line use.