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Machine Translation


User Stance Detection on Twitter


Meta-Learning for Few-Shot NMT Adaptation


Assisting Interpreters with Technical Terms

Abstract: To assist simultaneous interpreters with their work, one needs to find a balance between providing useful information and minimizing distraction. This talk will discuss a simple method for detecting and translating technical terms and a crowdsourced experiment to determine whether the method strikes the right balance for interpreter assistance--without actually using interpreters.


Lunch served by 12:15. 

Title: SCRIPTS: a System for Cross Language Information Processing,Translation and Summarization

Abstract: This presentation will give an overview of the research conducted by CLIP students and facuty to develop a System for Cross Language Information Processing, Translation and Summarization, as part of the IARPA MATERIAL program.

Title: Duolingo: Improving Language Learning and Assessment with Data

Title: Semantic and Stylistic Variations in Machine Translation

Abstract: While parallel texts represent invaluable resources for machine translation, they inevitably introduce biases in the cross-lingual mappings learned by machine translation models.  In addition to the domain bias and translationese bias studied in past work, we argue that another form of bias arises from subtle choices in content and style made by translators to appropriately convey the meaning of the source to their target audience.

A question-answering system designed by researchers from UMD and the University of Colorado holds its own against a top human team.


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