[PDF] Top 20 Neural Machine Translation of Logographic Language Using Sub character Level Information
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Neural Machine Translation of Logographic Language Using Sub character Level Information
... Neural machine translation (Cho et ...translations. Sub-word units are another tech- nique first introduced by Sennrich’s (2016) appli- cation of the byte pair encoding (BPE) algorithm, and ... See full document
9
Improving Character Based Decoding Using Target Side Morphological Information for Neural Machine Translation
... In this paper we proposed a new architecture to incorporate morphological information into the NMT pipeline. We extended the state-of-the-art NMT model (Chung et al., 2016) with a morphol- ogy table. The table ... See full document
11
Plan, Attend, Generate: Character Level Neural Machine Translation with Planning
... rent neural network (RNN) that reads the source (a sequence of byte pairs representing text in some lan- guage) and encodes it as a sequence of vector represen- tations; the decoder is a second RNN that generates ... See full document
7
Character based Neural Machine Translation
... the neural MT baseline system from (Bahdanau et ...the character- based neural language model (Kim et ...The translation unit continues to be the word, and we continue using word ... See full document
5
Sentence Level Agreement for Neural Machine Translation
... natural language processing tasks (Zhang et ...In neural machine translation (NMT), unlike conventional phrase-based statistical machine translation, an attention mechanism is ... See full document
7
A Simple and Effective Method for Injecting Word Level Information into Character Aware Neural Language Models
... natural language processing field, with various applications such as speech recognition (Mikolov et ...2010a), machine translation (Koehn, 2009) and summarization (Filippova et ...cently, ... See full document
9
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... German-Czech language pair are built based on the previously proposed unsupervised MT sys- tems, with some adaptations made to accom- modate the morphologically rich characteristics of German and Czech (Tsarfaty ... See full document
8
A Character Level Machine Translation Approach for Normalization of SMS Abbreviations
... distance using the web to generate a large set of automatically generated (noisy) pairs to be used for training and for spelling ...text using LM and dependency parse information. Machine ... See full document
9
Survey and Analysis on Language Translator using Neural Machine Translation
... use sub-word units for inputs and outputs in our system. Using sub-words gives a good balance between the flexibility of single characters and the efficiency of full words for decoding, and also ... See full document
7
Revisiting Character Based Neural Machine Translation with Capacity and Compression
... that should ideally be tuned for each language pair and corpus, an expensive step that is frequently omitted. Even when properly tuned, the repre- sentation of the corpus generated by pipelined external processing ... See full document
11
A Character Aware Encoder for Neural Machine Translation
... the character-level NMT model to solve many scalability issues, both in terms of computational speed and memory ...each character occurs frequently in the training corpus, all of the character ... See full document
8
Sub character Neural Language Modelling in Japanese
... the character level has proven useful in language modelling in English, as well as related applications such as build- ing word representations (Graves, 2013; Ling et ...in information re- ... See full document
6
Comparing Character level Neural Language Models Using a Lexical Decision Task
... the language model and its accuracy in the lex- ical decision task in Figure ...the character sequences that occurred in the test set, which are of course much more likely to be words than ...contextual ... See full document
6
How Grammatical is Character level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs
... trastive translation pairs for the assessment of neu- ral machine translation ...specific translation errors to the contrastive trans- lations, we gain valuable insight into the abil- ity of ... See full document
7
Document Level Adaptation for Neural Machine Translation
... We perform more detailed analysis across two kinds of novel words: those which should simply be copied from source to target (e.g. medication names) and those which must be translated. Ta- ble 5 shows results for the ... See full document
10
Neural Machine Translation into Language Varieties
... the opposite direction that presents the most rel- evant problems. First, languages varieties such as dialects might significantly overlap thus mak- ing differences among their texts quite subtle (e.g., particular ... See full document
9
A Character level Decoder without Explicit Segmentation for Neural Machine Translation
... prior information, if we use a neural net- work, be it recurrent, convolution or their combi- nation, directly on the unsegmented character se- ...of using a sequence of un- segmented ... See full document
11
Combining Character and Word Information in Neural Machine Translation Using a Multi Level Attention
... Table 5(b) shows two translation samples in- volving frequent words. For the compound word 被占领土 (beizhanlingtu, occupied territory), the baseline NMT system only partly translates the word as “occupation” and ... See full document
10
On the Importance of Word Boundaries in Character level Neural Machine Translation
... The translation problem is then modeled as a mapping between sequences of subword units in the source and target languages (Sennrich et ...the translation task in an end- to-end ...in sub- word ... See full document
7
Fully Character Level Neural Machine Translation without Explicit Segmentation
... fully character-level NMT model that maps a character sequence in a source language to a character sequence in a target ...purely character-level NMT model with a basic ... See full document
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