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The detection of emphatic words using acoustic and lexical features.

, , and . INTERSPEECH, page 3297-3300. ISCA, (2005)

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Parsing to Stanford Dependencies: Trade-offs between Speed and Accuracy., , , and . LREC, European Language Resources Association, (2010)Positive Diversity Tuning for Machine Translation System Combination., , and . WMT@ACL, page 320-328. The Association for Computer Linguistics, (2013)Fast and Adaptive Online Training of Feature-Rich Translation Models., , , and . ACL (1), page 311-321. The Association for Computer Linguistics, (2013)SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability., , , , , , , , , and 3 other author(s). SemEval@NAACL-HLT, page 252-263. The Association for Computer Linguistics, (2015)SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity., , , and . SemEval@NAACL-HLT, page 385-393. The Association for Computer Linguistics, (2012)Learning Alignments and Leveraging Natural Logic., , , , , , , , , and . ACL-PASCAL@ACL, page 165-170. Association for Computational Linguistics, (2007)Measuring machine translation quality as semantic equivalence: A metric based on entailment features., , , , and . Mach. Transl., 23 (2-3): 181-193 (2009)Robust Graph Alignment Methods for Textual Inference and Machine Reading., , , , , , and . AAAI Spring Symposium: Machine Reading, page 36-42. AAAI, (2007)Neural mechanisms of binding in the hippocampus and neocortex: insights from computational models., and . Handbook of Binding and Memory, Oxford University Press, (2006)*SEM 2013 shared task: Semantic Textual Similarity., , , , and . *SEM@NAACL-HLT, page 32-43. Association for Computational Linguistics, (2013)