IWSLT

ISI entered two statistical machine translation systems in the IWSLT evaluation this year: one was phrase-based and the other syntax-based. The syntax-based system represents the results of a current research …...

This paper provides a description of TALP-Ngram, the tuple-based statistical machine translation system devel- oped at the TALP Research Center of the UPC (Univer- sitat Polit`ecnica de Catalunya). Briefly, the …...

AbstractThis paper presents the University of Washington’s submission to the 2007 IWSLT benchmark evaluation. The UW system participated in two data tracks, Italian-to-English and Arabic-to-English. Our main focus was on …...

The translation model of statistical ma- chine translation systems is trained on par- allel data coming from various sources and domains. These corpora are usually con- catenated, word alignments are …...

Punctuations are not available in automatic speech recognition outputs, which could cre- ate barriers to many subsequent text pro- cessing tasks. This paper proposes a novel method to predict punctuation …...

When machine translation researchers par- ticipate in evaluation tasks, they typically design their primary submissions using ideas that are not genre-specific. In fact, their systems look much the same from …...

We propose a conversion of bilingual sentence pairs and the corresponding word alignments into novel linear se- quences. These are joint translation and reordering (JTR) uniquely defined sequences, combining interdepending …...

AbstractNeural machine translation systems require a number of stacked layers for deep models. But the prediction depends on the sentence representation of the top-most layer with no access to low-level …...

Memory-augmented neural networks (MANNs) have been shown to outper- form other recurrent neural network architectures on a series of artificial sequence learning tasks, yet they have had limited application to …...

AbstractNeural Networks trained with gradient descent are known to be susceptible to catastrophic forgetting caused by parameter shift during the training process. In the context of Neural Machine Translation (NMT) …...

AbstractMultilingual neural machine translation with a single model has drawn much attention due to its capability to deal with multiple languages. However, the current multilingual translation paradigm often makes the …...

AbstractSimultaneous machine translation has recently gained traction thanks to significant quality improvements and the advent of streaming applications. Simultaneous translation systems need to find a trade-off between translation quality and …...

AbstractRecently, non-autoregressive (NAR) neural machine translation models have received increasing attention due to their efficient parallel decoding. However, the probabilistic framework of NAR models necessitates conditional independence assumption on target …...