2014 OnthePropertiesofNeuralMachineT

• (Cho et al., 2014) ⇒ Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, and Yoshua Bengio. (2014). "On the Properties of Neural Machine Translation: Encoder-Decoder Approaches". In: Proceedings of Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST@EMNLP 2014). DOI:10.3115/v1/W14-4012

Subject Headings: Encoder-Decoder Network, Neural Machine Translation.

Notes

• Version(s) & URL(s):
  • ArXiv: https://arxiv.org/abs/1409.1259
  • DBLP: https://dblp.org/rec/conf/ssst/ChoMBB14.html

Cited By

• Google Scholar: ~ 2,372 Citations. Retrieved: 2020-04-12.
• Semantic Scholar: ~ 2,004 Citations. Retrieved: 2020-04-12.
• MS Academic: ~ 2,219 Citations. Retrieved: 2020-04-12.

Quotes

Abstract

Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a decoder. The encoder extract]]s a fixed-length representation from a variable-length input sentence, and the decoder generates a correct translation from this representation. In this paper, we focus on analyzing the properties of the neural machine translation using two models; RNN Encoder-“Decoder and a newly proposed gated recursive convolutional neural network. We show that the neural machine translation performs relatively well on short sentences without unknown words, but its performance degrades rapidly as the length of the sentence and the number of unknown words increase. Furthermore, we find that the proposed gated recursive convolutional network learns a grammatical structure of a sentence automatically.

BibTeX

@inproceedings{2014_OnthePropertiesofNeuralMachineT,
  author    = {Kyunghyun Cho and
               Bart van Merrienboer and
 [[Dzmitry Bahdanau]] and
 [[Yoshua Bengio]]},
  editor    = {Dekai Wu and
               Marine Carpuat and
               Xavier Carreras and
               Eva Maria Vecchi},
  title     = {On the Properties of Neural Machine Translation: Encoder-Decoder Approaches},
  booktitle = {Proceedings of Eighth Workshop on Syntax, Semantics
               and Structure in Statistical Translation (SSST@EMNLP 2014), Doha, Qatar, 25 October
               2014},
  pages     = {103--111},
  publisher = {Association for Computational Linguistics},
  year      = {2014},
  url       = {https://www.aclweb.org/anthology/W14-4012.pdf},
  doi       = {10.3115/v1/W14-4012},
}

---

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 OnthePropertiesofNeuralMachineT	Yoshua Bengio Kyunghyun Cho Bart van Merrienboer Dzmitry Bahdanau			On the Properties of Neural Machine Translation: Encoder-Decoder Approaches						2014