[PDF] Top 20 Stochastic K TSS Bi Languages for Machine Translation

... on bi-lingual units as proposed in (Bangalore and Riccardi, 2002) for ...of bi-lingual ...for machine translation pur- poses can be found (Bangalore and Riccardi, 2002) (Oncina et ...of ... See full document

... by stochastic regular bi- languages. These languages have also been success- fully proposed to deal with machine translation (Tor- res and Casacuberta, ...State ... See full document

... • Stochastic word ...a stochastic word match- ing in the string alignment instead of WORD- STEM and WORD-NET used in METEOR and ...1993). Stochastic word matching is a uniform replacement for both ... See full document

... vidual model scores were re-optimized. Table 4 shows the evaluation results on the dev set. Since the BLEU score alone is often not a good indi- cator of successful translations of unknown words (the unigram or bigram ... See full document

... language. Machine Translation activities in India are relatively young and their demand is increasing due to increased exchange of information on internet across the world, due to which machine ... See full document

... We use the techniques described by Johnson et al. (2017) to build a multilingual model that combines forward and backward directions of a single lan- guage pair. To begin, we construct training data by swapping the ... See full document

... den state (or 512 for each direction in the bidirec- tional LSTMs) and 256 for the attention mechan- sim. Training is done with Adam (Kingma and Ba, 2015). In decoding we use a beam of size 5 and output the most likely ... See full document

... The translation of natural language by machine becomes a reality, for technologically favored languages, in the late 20th century although it is dreamt since the seventieth century (Hutchins, ... See full document

... As with other low-resourced and inflected lan- guages, Gaelic languages suffer from data sparsity. While other language pairs can achieve high trans- lation accuracy using state-of-the-art data-hungry methods, ... See full document

... We tested several various combinations of tags, while using a single translation component. Some combinations seem to be affected by sparse data problems and the best score is achieved by using both person and ... See full document

... Machine translation systems are often only evalu- ated quantitatively by using automatic metrics, such as Bleu (Papineni et ...for translation out of English (Callison-Burch et ... See full document

... We received good response from researchers worldwide and based on reviews from our strong program committee 4 papers were accepted for oral presentation (long papers) and 9 papers for poster presentation (short papers). ... See full document

... Many works generate and harness paraphrases (Barzilay and McKeown, 2001; Pang et al., 2003; Callison-Burch et al., 2005; Mallinson et al., 2017; Ganitkevitch et al., 2013; Brad and Rebedea, 2017; Quirk et al., 2004; ... See full document

... featured translation task of the Sixth Work- shop on Statistical Machine Translation, we devel- oped a system for translating Haitian Creole Emer- gency SMS ...statistical machine trans- ... See full document

... English translation, the idea is to use the target language model to validate changes of struc- ture, instead of writing source language dependent mapping ... See full document

... two translation steps served dif- ferent functions: The first step made a sme text for a concrete set of readers in a concrete setting, whereas the last step was part of a decontextualised evaluation ... See full document

... As shown in Table 1, our proposed model out- performs different baselines on all sets, which ver- ifies that the chunk-based bi-scale decoder is ef- fective for NMT. Our model gives a 1.6 BLEU score improvement ... See full document

... Tables 10 and 11 show the percent of times that the metrics’ scores were consistent with human rank- ings of every pair of translated sentences. 7 Since we eliminated sentence pairs that were judged to be equal, the ... See full document

... This year we excluded Google translations from the systems used in system combina- tion. In last year’s evaluation, the large mar- gin between Google and many of the other systems meant that it was hard to improve on ... See full document

... This paper describes LIMSI’s participation to the first shared task on Native Language Iden- tification. Our submission uses a Maximum Entropy classifier, using as features character and chunk n-grams, spelling and ... See full document