Decoding Algorithm

method ID: decodingalgorithm

Related Papers

Fast Decoding and Optimal Decoding for Machine Translation

Authors: nan

Publication: TIPSTER (2001)

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A good decoding algorithm is critical to the success of any statistical machine translation system. The decoder’s job is to find the translation that is most likely according to set …...

35310

Statistical Phrase-Based Translation

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Publication: TIPSTER (2003)

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We propose a new phrase-based translation model and decoding algorithm that enables us to evaluate and compare several, previ- ously proposed phrase-based translation mod- els. Within our framework, we carry …...

24042

Multi-engine machine translation guided by explicit word matching

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. We describe a new approach for synthetically combining the output of several different Machine Translation (MT) engines operating on the same input. The goal is to pro- duce a …...

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Modeling Cantonese Pronunciation Variations for Large-Vocabulary Continuous Speech Recognition

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Publication: TIPSTER (2006)

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This paper presents different methods of handling pronunciation variations in Cantonese large-vocabulary continuous speech recognition. In an LVCSR system, three knowledge sources are involved: a pronunciation lexicon, acoustic models and …...

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Kernel Regression Framework for Machine Translation: UCL System Description for WMT 2008 Shared Translation Task

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The novel kernel regression model for SMT only demonstrated encouraging results on small-scale toy data sets in previous works due to the complexities of kernel methods. It is the first …...

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Data-driven Multilingual Coreference Resolution using Resolver Stacking

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This paper describes our contribution to the CoNLL 2012 Shared Task.1 We present a novel decoding algorithm for coreference res- olution which is combined with a standard pair-wise coreference resolver …...

42228

Joint Chinese Word Segmentation, POS Tagging and Parsing

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Publication: TIPSTER (2012)

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In this paper, we propose a novel decoding al- gorithm for discriminative joint Chinese word segmentation, part-of-speech (POS) tagging, and parsing. Previous work often used a pipeline method – Chinese …...

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Trainable Greedy Decoding for Neural Machine Translation

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AbstractRecent research in neural machine translation has largely focused on two aspects; neural network architectures and end-to-end learning algorithms. The problem of decoding, however, has received relatively little attention from …...

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AbstractMetaphor generation attempts to replicate human creativity with language, which is an attractive but challengeable text generation task. Previous efforts mainly focus on template-based or rule-based methods and result in …...

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Language Model Decoding as Likelihood–Utility Alignment

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AbstractA critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm remain unclear. Previous works …...

33343