For current statistical machine translation system, reordering is still a major problem for language pairs like Chinese-English, where the source and target language have significant word order differences. In this pa...
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In this paper, we consider the use of multiple acoustic features of the speech signal for robust speech recognition. We investigate the combination of various auditory based (Mel Frequency Cepstrum Coefficients, Perce...
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作者：
Saers, MarkusWu, DekaiHKUST
Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong
We show that there are situations where iteratively segmenting sentence pairs top-down will fail to reach valid segments and propose a method for alleviating the problem. Due to the enormity of the search space, error...
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In this paper the statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of the International Workshop on Spoken language Translation (IWSLT) 2011 is presented. W...
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We introduce the first fully automatic, fully semantic frame based MT evaluation metric, MEANT, that outperforms all other commonly used automatic metrics in correlating with human judgment on translation adequacy. Re...
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In this work we release our extensible and easily configurable neural network training software. It provides a rich set of functional layers with a particular focus on efficient training of recurrent neural network to...
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The most widely used acoustic feature extraction methods of current automatic speech recognition (ASR) systems are based on the assumption of stationarity. In this paper we extensively evaluate a recently introduced f...
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The HKUST word sense disambiguation systems benefit from a new nonlinear Kernel Principal Component Analysis (KPCA) based disambiguation technique. We discuss and analyze results from the Senseval-3 English, Chinese, ...
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German is a highly inflected language with a large number of words derived from the same root. It makes use of a high degree of word compounding leading to high Out-of-vocabulary (OOV) rates, and language Model (LM) p...
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作者：
Wu, DekaiChi-Kiu, LoSaers, MarkusHKUST
Human Language Technology Center Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong
We examine lexical access preferences and constraints in computing multiword expression associations from the standpoint of a high-impact extrinsic task-based performance measure, namely semantic machine translation e...
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