Olivia Buzek


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Learning to translate with products of novices: a suite of open-ended challenge problems for teaching MT
Adam Lopez | Matt Post | Chris Callison-Burch | Jonathan Weese | Juri Ganitkevitch | Narges Ahmidi | Olivia Buzek | Leah Hanson | Beenish Jamil | Matthias Lee | Ya-Ting Lin | Henry Pao | Fatima Rivera | Leili Shahriyari | Debu Sinha | Adam Teichert | Stephen Wampler | Michael Weinberger | Daguang Xu | Lin Yang | Shang Zhao
Transactions of the Association for Computational Linguistics, Volume 1

Machine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them are best learned by doing. As a centerpiece of our MT course, we devised a series of open-ended challenges for students in which the goal was to improve performance on carefully constrained instances of four key MT tasks: alignment, decoding, evaluation, and reranking. Students brought a diverse set of techniques to the problems, including some novel solutions which performed remarkably well. A surprising and exciting outcome was that student solutions or their combinations fared competitively on some tasks, demonstrating that even newcomers to the field can help improve the state-of-the-art on hard NLP problems while simultaneously learning a great deal. The problems, baseline code, and results are freely available.


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The Value of Monolingual Crowdsourcing in a Real-World Translation Scenario: Simulation using Haitian Creole Emergency SMS Messages
Chang Hu | Philip Resnik | Yakov Kronrod | Vladimir Eidelman | Olivia Buzek | Benjamin B. Bederson
Proceedings of the Sixth Workshop on Statistical Machine Translation


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Crowdsourcing the evaluation of a domain-adapted named entity recognition system
Asad B. Sayeed | Timothy J. Meyer | Hieu C. Nguyen | Olivia Buzek | Amy Weinberg
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

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Error Driven Paraphrase Annotation using Mechanical Turk
Olivia Buzek | Philip Resnik | Ben Bederson
Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk

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Improving Translation via Targeted Paraphrasing
Philip Resnik | Olivia Buzek | Chang Hu | Yakov Kronrod | Alex Quinn | Benjamin B. Bederson
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing