Dennis Mehay

Also published as: Dennis Nolan Mehay


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Anticipatory translation model adaptation for bilingual conversations
Sanjika Hewavitharana | Dennis Mehay | Sankaranarayanan Ananthakrishnan | Rohit Kumar | John Makhoul
Proceedings of the 11th International Workshop on Spoken Language Translation: Papers

Conversational spoken language translation (CSLT) systems facilitate bilingual conversations in which the two participants speak different languages. Bilingual conversations provide additional contextual information that can be used to improve the underlying machine translation system. In this paper, we describe a novel translation model adaptation method that anticipates a participant’s response in the target language, based on his counterpart’s prior turn in the source language. Our proposed strategy uses the source language utterance to perform cross-language retrieval on a large corpus of bilingual conversations in order to obtain a set of potentially relevant target responses. The responses retrieved are used to bias translation choices towards anticipated responses. On an Iraqi-to-English CSLT task, our method achieves a significant improvement over the baseline system in terms of BLEU, TER and METEOR metrics.

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Lightly-Supervised Word Sense Translation Error Detection for an Interactive Conversational Spoken Language Translation System
Dennis Mehay | Sankaranarayanan Ananthakrishnan | Sanjika Hewavitharana
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers


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Source aware phrase-based decoding for robust conversational spoken language translation
Sankaranarayanan Ananthakrishnan | Wei Chen | Rohit Kumar | Dennis Mehay
Proceedings of the 10th International Workshop on Spoken Language Translation: Papers

Spoken language translation (SLT) systems typically follow a pipeline architecture, in which the best automatic speech recognition (ASR) hypothesis of an input utterance is fed into a statistical machine translation (SMT) system. Conversational speech often generates unrecoverable ASR errors owing to its rich vocabulary (e.g. out-of-vocabulary (OOV) named entities). In this paper, we study the possibility of alleviating the impact of unrecoverable ASR errors on translation performance by minimizing the contextual effects of incorrect source words in target hypotheses. Our approach is driven by locally-derived penalties applied to bilingual phrase pairs as well as target language model (LM) likelihoods in the vicinity of source errors. With oracle word error labels on an OOV word-rich English-to-Iraqi Arabic translation task, we show statistically significant relative improvements of 3.2% BLEU and 2.0% METEOR over an error-agnostic baseline SMT system. We then investigate the impact of imperfect source error labels on error-aware translation performance. Simulation experiments reveal that modest translation improvements are to be gained with this approach even when the source error labels are noisy.

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Incremental Topic-Based Translation Model Adaptation for Conversational Spoken Language Translation
Sanjika Hewavitharana | Dennis Mehay | Sankaranarayanan Ananthakrishnan | Prem Natarajan
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)


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CCG Syntactic Reordering Models for Phrase-based Machine Translation
Dennis Nolan Mehay | Christopher Hardie Brew
Proceedings of the Seventh Workshop on Statistical Machine Translation


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Semantic Role Labeling Without Treebanks?
Stephen Boxwell | Chris Brew | Jason Baldridge | Dennis Mehay | Sujith Ravi
Proceedings of 5th International Joint Conference on Natural Language Processing


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What a Parser Can Learn from a Semantic Role Labeler and Vice Versa
Stephen Boxwell | Dennis Mehay | Chris Brew
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing


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Refining the most frequent sense baseline
Judita Preiss | Jon Dehdari | Josh King | Dennis Mehay
Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions (SEW-2009)

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Brutus: A Semantic Role Labeling System Incorporating CCG, CFG, and Dependency Features
Stephen Boxwell | Dennis Mehay | Chris Brew
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP


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Hypertagging: Supertagging for Surface Realization with CCG
Dominic Espinosa | Michael White | Dennis Mehay
Proceedings of ACL-08: HLT

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OSU-2: Generating Referring Expressions with a Maximum Entropy Classifier
Emily Jamison | Dennis Mehay
Proceedings of the Fifth International Natural Language Generation Conference