6533b7d0fe1ef96bd125b051

RESEARCH PRODUCT

Translingual text mining for identification of language pair phenomena

Jolanta Mizera-pietraszko

subject

Machine translationLanguage identificationComputer sciencebusiness.industry05 social sciencessimilarity metrics02 engineering and technologycomputer.software_genre050105 experimental psychologycomputational linguisticsmultilingual information retrievalUniversal Networking LanguageCache language modelLanguage technology0202 electrical engineering electronic engineering information engineeringComputer-assisted translation020201 artificial intelligence & image processing0501 psychology and cognitive sciencesinformation extractionLanguage modelArtificial intelligencebusinesscomputerLanguage industryNatural language processing

description

Translingual Text Mining (TTM) is an innovative technology of natural language processing for building multilingual parallel corpora, processing machine translation, contextual knowledge acquisition, information extraction, query profiling, language modeling, contextual word sensing, creating feature test sets and for variety of other purposes. The Keynote Lecture will discuss opportunities and challenges of this computational technology. In particular, the focus will be made on identification of language pair phenomena and their applications to building holistic language model which is a novel tool for processing machine translation, supporting professional translations, evaluation of translingual systems efficiency and also for improving the process of teaching foreign languages regardless of the level of students' proficiency. Some components incorporated to machine translation systems rely specifically on language-pair phenomena like for example language recognizer, or word deliminer. Nowadays, declarative programming is becoming widely used just for describing language pair phenomena by graphical formalism. Translation irreversibility represents a unique language and system independent asymmetrical translation innovative technology, which will be presented during the Keynote lecture.

https://doi.org/10.1109/intech.2016.7845138