[PDF] Top 20 Trait Based Hypothesis Selection For Machine Translation

... In this paper, we show it is possible to create diverse input hypotheses for combination without making any algorithmic changes. Instead, we use traits, which are very simple attributes of the MT output, such as “output ... See full document

... counts based on such Web documents are ...systems based on Web counts to produce more errors than our sys- tems ...systems based on fea- tures mined from the Web were able to achieve the best ...tems ... See full document

... automatic translation, such as word and n-gram statistics, POS statistics, and syntactic features; and (ii) glass box fea- tures, which also use internal information from the transla- tion ...our selection ... See full document

... subset selection, generalizing previous approaches to this ...data selection methods on two different trans- lation ...subset selection is applicable to other data sets that can be represented as ... See full document

... multi-engine machine trans- lation has also been performed in recent ...The selection is made based on the scores of translation, language, and other mod- els (Nomoto, 2004; Paul et ...chine ... See full document

... In this paper, we propose an indirect hidden Markov model (IHMM) for MT hypothesis alignment. The HMM provides a way to model both synonym matching and word ordering. Unlike traditional HMMs whose parameters are ... See full document

... ence, we found the tense of the verb phrases in the Hindi reference to be different from that of En- glish. Also, often the presence of auxiliary verbs ‘hona’ in the Hindi reference changed the struc- ture of the verb ... See full document

... The MERS models combines rich contextual in- formation as features to help the decoder perform rule selection. Table 4 shows the effect of different feature sets. We test two classes of feature sets: the single ... See full document

... A potential downside of this approach reveals it- self when there is redundancy in the candidate pool. Since the batch is selected in a single atomic opera- tion from the sorted candidates, and because similar or ... See full document

... To analyze the influence of different features, we trained the MERS model using source-side and target-side n-gram lexical features similar to the CSRS model. When using this feature set, the performance of the MERS ... See full document

... G?HI JLKNM OPMH?QSRUTVWA0DX@YO[Z.[r] ... See full document

... Lexical selection is of great importance to statistical machine ...lexical selection. The framework is established on a translation graph that captures not only local associ- ations between ... See full document

... Intelligent selection of training data has proven a successful technique to simul- taneously increase training efficiency and translation performance for phrase-based machine ... See full document

... all than the computation that would be spent us- ing all available corpora while still achieve SMT performance that is close to the top performing phrase-based SMT systems. ParFDA results at WMT16 provides new ... See full document

... a machine translation task. The system used in this test is based upon MOSES, briefly described in (Koehn et ...a translation table, a language model, a distortion model and a penality which ... See full document

... a hypothesis regeneration pass is added between the decoding and rescoring ...ated based on the original N-best hypotheses through n-gram expansion, confusion-network decoding or ...three hypothesis ... See full document

... presents hypothesis mixture decoding (HM decoding), a new decoding scheme that performs translation reconstruction using hypo- theses generated by multiple translation ...best translation from ... See full document

... Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation Qun Liu, Zhongjun He, Yang Liu and Shouxun Lin.. Indirect-HMM-based Hypothesis Alignment for C[r] ... See full document

... crowdsourcing machine learning prob- lems: rather than competing, everyone works to- gether to solve a shared task, with credit awarded proportional to the contribution that each individual ... See full document

... We used 1 million sentence pairs that are con- tained in train-1.txt of ASPEC-JE corpus for training the translation rule tables and NMT models. We also used 3 million Japanese sen- tences that are contained in ... See full document