[PDF] Top 20 Integrating an Unsupervised Transliteration Model into Statistical Machine Translation

... a transliteration system from mined corpus, we built it using the gold standard corpus (for Arabic, Hindi and Russian), that we also used previously to do an intrinsic ...mined transliteration systems with ... See full document

... linear model were optimized with MIRA (Watan- abe et ...baseline model to produce query translations and hypergraphs for the cross-lingual retrieval of target matches as well as to produce 500-best lists, ... See full document

... Arabic statistical machine translation quality. Machine Transla- tion has been defined as the process that utiliz- es computer software to translate text from one natural language to ... See full document

... channel model on the transliteration task into a multi-to-multi joint source-channel model, which allows alignments between substrings of arbitrary lengths in both source and target ...the ... See full document

... Morfessor, which gives state of the art results in many tests (Kurimo et al., 2009), uses only mono- lingual information in its objective function. It is conceivable that we can achieve a better segmenta- tion for ... See full document

... language model (LM) log probability for each name from the target side of the training data corpus to ensure that the gener- ated candidate is a fluent target name; the second feature is the string edit distance ... See full document

... pronoun-focused translation task at DiscoMT 2015 is a document-level phrase-based statistical ma- chine translation (SMT) system integrating a neu- ral network classifier for pronoun ...level ... See full document

... English transliteration). Secondly, the joint mul- tigram model relies on key features not present in the SMT system, that is the history of bilin- gual phrase pairs used to derive the ... See full document

... Statistical transliteration can address these chal- lenges by learning transliteration divergences from a parallel transliteration ...parallel transliteration corpora are not publicly ... See full document

... phrase transliteration system achieves 90% exact match accuracy on 500 unique name pairs, utilizing all of the phrase decoder feature functions except for distortion ... See full document

... level translation probabilities using the lexical translation probabilities learned by mgiza during the training of our USMT ...language model used by our USMT system while the other is a small ... See full document

... in translation quality (Nakov et ...about unsupervised transliteration mining and its incorporation to the GIZA++ word ...the transliteration sys- ...sian/English machine ... See full document

... Statistical alignment methods used in machine translation are relevant in our context if we consider that the target language is the concept language. There are nevertheless differences with genuine ... See full document

... hybrid machine translit- eration method, which combines statistical model and web search for transliterating names in various ...phrase-based statistical machine translation ... See full document

... In order to overcome these limitations, we pro- pose an iterative refinement procedure based on backtranslation (Sennrich et al., 2016). More con- cretely, we generate a synthetic parallel corpus by translating the ... See full document

... Neural Machine Trans- lation model (Sennrich et ...the model performance. In this technique, a model is initially trained in one of the direc- tions (say target to source) and the trained ... See full document

... (Zhao et al., 2004) tackle LM adaptation for SMT. Similarly to our work, they use automati- cally generated hypotheses to perform adaptation. We extend their work by using the hypotheses also for TM adaptation. ... See full document

... Statistical Machine Translation depends of huge amount of parallel text to generate translations from source to target ...some statistical models it outputs the best possible ...the ... See full document

... For this task, we trained a Tajik POS tagger using the Farsi POS-tagged Bijankhan Corpus that we transliterated into Tajik. The training was done using a Maximum Entropy model tagger (Ratnaparkhi, 1996). The tag ... See full document

... proposed transliteration scheme uses grapheme based method to model the transliteration ...demonstrated transliteration from Punjabi to English for common names and achieved accuracy of ... See full document