We propose a tracking adaptation to recover from early tracking errors in sign languagerecognition by optimizing the obtained tracking paths w.r.t. the hypothesized word sequences of an automatic sign language recogn...
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This paper compares different neural network based architectures on the spoken language identification task. To our best knowledge such a comparison of different models on the same dataset and the same set of language...
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Punctuation prediction is an important task in Spoken language Translation. The output of speech recognition systems does not typically contain punctuation marks. In this paper we analyze different methods for punctua...
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Domain adaptation for statistical machine translation is the task of altering general models to improve performance on the test domain. In this work, we suggest several novel weighting schemes based on translation mod...
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In this paper, we investigate different methodologies of Arabic segmentation for statistical machine translation by comparing a rule-based segmenter to different statistically-based segmenters. We also present a new m...
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The task of domain-adaptation attempts to exploit data mainly drawn from one domain (e.g. news) to maximize the performance on the test domain (e.g. weblogs). In previous work, weighting the training instances was use...
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We present a demonstration of a neural interactive-predictive system for tackling mul- timodal sequence to sequence tasks. The sys- tem generates text predictions to different se- quence to sequence tasks: machine tra...
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The increasing popularity of statistical machine translation (SMT) systems is introducing new domains of translation that need to be tackled. As many resources are already available, domain adaptation methods can be a...
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In this paper, we present two improvements to the beam search approach for solving homophonic substitution ciphers presented in Nuhn et al. (2013): An improved rest cost estimation together with an optimized strategy ...
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