[PDF] Top 20 Minimum Error Rate Training by Sampling the Translation Lattice

... growing translation pools is based on the key observation that BLEU only de- pends on the single translation receiving the highest score by the translation model (which would be the one shown to the ... See full document

... achievable error rate for a classifier with an additional constraint of a given structure ...for training a nonlinear classifier with given ...Carlo sampling method ...these training ... See full document

... Machine Translation (SMT) systems have improved considerably by directly using the error criterion in both training and ...the translation task instead of a criterion such as like- lihood that ... See full document

... machine translation, minimum error rate training (MERT) is a standard method for tuning a single weight with regard to a given development ...local training method to address ... See full document

... a translation candidate e s,m is proportional to (exp (w | h s,m )) µ , where w are the parameters be- ing optimized, h s,m is the vector of the features ... See full document

... unsmoothed error surface has a special property that enables exact search: the set of translations produced by an SMT system for a given input is finite, so the piecewise-constant error surface contains ... See full document

... machine translation (MT) systems over the past few years (Och and Ney, 2002; Koehn et ...candidate translation in the target ...didate translation, as scored by the different model components, and ... See full document

... target-to-source translation models, word and rule penalties, number of usages of the glue rule, word deletion scale factor, source-to-target and target-to- source lexical models, and three count-based fea- tures ... See full document

... To perform an iterative parameter update with MERT, it is necessary to evaluate the system trans- lation quality given by the current weights by the translation metric to be optimized. This process obviously ... See full document

... correct translation might not be among the can- didates that our MT system ...the minimum word-error rate as pseudo reference ...word-error rate. Here, we will use the ... See full document

... The recent work of Jiampojamarn et al (2007) combines both of the above approaches in a very in- teresting manner. It uses an EM like algorithm for aligning the letters and phonemes. The algorithm al- lows many-to-many ... See full document

... machine translation for morphologically rich languages using a hybrid morpheme-word representation where the basic unit of translation is the morpheme, but word boundaries are respected at all stages of the ... See full document

... Abstract- Joshua, an open source toolkit for statistical machine translation. It implements all of the algorithms required for synchronous context free grammars (SCFGs): chart-parsing, n-gram language model ... See full document

... Minimum error rate training is often the pre- ferred method for optimizing parameters of statistical machine translation ...minimizes error rate by using a surrogate rep- ... See full document

... discriminative training step in the development of large MT sys- tems — learning the log-linear combination of sev- eral component model scores (viewed as features) to optimize a performance metric ...tive ... See full document

... the lattice variant of Och’s procedure did not typ- ically exceed those for the n-best variant on de- velopment data, on test data the lattice variant out- performed the n-best approach by between ...the ... See full document

... As shown in Algorithm 2, the T-MERT algo- rithm could be divided into two loops: in the out- er loop (outer-translation step), the test dataset is translated under current weight and new pseudo labeled test ... See full document

... alternative translation hypotheses represented in a lattice also increases the number of phase transitions in the error surface, and thus prevents MERT from selecting a low performing feature weights ... See full document

... the training procedure for statisti- cal machine translation models is based on maximum likelihood or related ...final translation quality on unseen ...various training criteria which directly ... See full document

... We believe that our results show very convinc- ingly that using random restarts in MERT im- proves the B LEU scores produced by the result- ing models. They also seem to show that starting point selection by random walk ... See full document