[PDF] Top 20 Multimodal Machine Translation with Embedding Prediction
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Multimodal Machine Translation with Embedding Prediction
... Translation Examples In Table 4, we show French-English translations generated by different models. In the left example, our proposed model correctly translates “voˆute” into “archway” (oc- curs five times in the ... See full document
6
Full Network Embedding in a Multimodal Embedding Pipeline
... In the last few years, several solutions have been proposed to the problem of building common repre- sentations for images and text with the goal of enabling cross-domain search [1, 2, 3, 4, 5]. This paper builds upon ... See full document
9
Probing the Need for Visual Context in Multimodal Machine Translation
... Hyperparameters. The encoder and decoder GRUs have 400 hidden units and are initialized with 0 except the multimodal INIT system. All embeddings are 200-dimensional and the decoder embeddings are tied (Press and ... See full document
12
Debiasing Word Embeddings Improves Multimodal Machine Translation
... However, when word embeddings are used in the k-nearest neighbor (kNN) problem, certain words appear frequently in the k-nearest neighbors for other words (Dinu et al., 2015; Faruqui et al., 2016); this is called the ... See full document
11
A Visual Attention Grounding Neural Model for Multimodal Machine Translation
... chine Translation (VAG-NMT) to leverage visual information more ...a translation model, and (2) constructing a vision-language joint semantic ...shared embedding space to initial- ize the ... See full document
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A Shared Task on Multimodal Machine Translation and Crosslingual Image Description
... for multimodal machine translation task, since BiRNNs can deal with images and ...most translation systems the same word embedding is fed to both BiRNN ... See full document
11
OSU Multimodal Machine Translation System Report
... neural-based machine translation model, the encoder needs to map sequence of word embeddings from the source side into an- other representation of the entire sequence us- ing recurrent ... See full document
5
Sheffield MultiMT: Using Object Posterior Predictions for Multimodal Machine Translation
... a lower-level image representation directly to the model, such work explicitly explores predicting the occurrence of various concepts (objects, also referred to as attributes) in the image, and feeding such predictions ... See full document
7
Findings of the Third Shared Task on Multimodal Machine Translation
... 10-best translation candidates of German-Czech, French-Czech and English-Czech neural MT systems and then re-ranks them using the same multimodal cross-lingual WSD model as in Task ...neural machine ... See full document
20
Proceedings of the First Conference on Machine Translation: Volume 1, Research Papers
... five translation tasks: Machine Translation of News, Machine Translation of IT domain, Biomedical Translation, Multimodal Machine Translation, and ... See full document
28
Knowledge Based Semantic Embedding for Machine Translation
... a translation is right by main information and grammar correction, we la- bel it as correct translation, no matter how differ- ent of the translation compared with the reference on surface ...correct ... See full document
10
An empirical study on the effectiveness of images in Multimodal Neural Machine Translation
... Soft attention has firstly been used for syntactic constituency parsing by Vinyals et al. (2015) but has been widely used for translation tasks ever since. One should note that it slightly differs from Bahdanau et ... See full document
10
Proceedings of the Third Conference on Machine Translation: Research Papers
... Statistical Machine Translation was held at ACL 2007 in Prague, Czech Republic, ACL 2008, Columbus, Ohio, USA, EACL 2009 in Athens, Greece, ACL 2010 in Uppsala, Sweden, EMNLP 2011 in Edinburgh, Scotland, ... See full document
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Multimodal Neural Machine Translation for Low resource Language Pairs using Synthetic Data
... ral machine translation (NMT) and image de- scription generation (IDG) that explicitly uses an encoder-decoder framework as an instan- tiation of the sequence to sequence (seq2seq) learning problem (Cho et ... See full document
10
Robust Neural Machine Translation with Joint Textual and Phonetic Embedding
... jointly embedding both textual and phonetic information of source sentences, and 2) aug- menting the training dataset with homophone ...the translation quality on some clean test ... See full document
6
Prediction of Learning Curves in Machine Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Con- stantin, and Evan ... See full document
9
Multilingual Multimodal Machine Translation for Dravidian Languages utilizing Phonetic Transcription
... cases, machine translation can be a useful tool for the quick ex- pansion to new languages by producing candidate translation (Dutta Chowdhury et ...Statistical Machine Translation ... See full document
8
Urdu to English Machine Translation using Bilingual Evaluation Understudy
... for translation is much larger than one ...repetitive translation and improvements by human annotators and translators contribute significantly to any MT ... See full document
8
INMT: Interactive Neural Machine Translation Prediction
... teractive translation system between English and five Indic languages (Bengali, Hindi, Malayalam, Tamil and Telugu) using state-of-the-art NMT ...the translation suggestions in real ... See full document
6
A Structured Prediction Approach for Statistical Machine Translation
... Statistical Machine Translation (SMT) is attract- ing more attentions than rule-based and example- based methods because of the availability of large training corpora and automatic ... See full document
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