Tag Archives: OpenNMT

Some Useful Links on Neural Machine Translation

Some good resources for NNMT

Tutorial:

a bit special: Tensor2Tensor uses a novel architecture instead of pure RNN/CNN decoder/encoder.   It gives a surprisingly large amount of gain.  So it's likely that it will become a trend in NNMT in the future.

Important papers:

  • Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation by Cho Et al. (link) - Very innovative and smart paper by Kyunghyun Cho.  It also introduces GRU.
  • Sequence to Sequence Learning with Neural Networks by Ilya Sutskever (link) - By Google's researchers, and perhaps it shows for the first time an NMT system is comparable to the traditional pipeline.
  • Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation (link)
  • Neural Machine Translation by Joint Learning to Align and Translate by Dzmitry Bahdanau (link) - The paper which introduce attention
  • Neural Machine Translation by Min-Thuong Luong (link)
  • Effective Approaches to Attention-based Neural Machine Translation by Min-Thuong Luong (link) - On how to improve attention approach based on local attention.
  • Massive Exploration of Neural Machine Translation Architectures by Britz et al (link)
  • Recurrent Convolutional Neural Networks for Discourse Compositionality by Kalchbrenner and Blunsom (link)

Important Blog Posts/Web page:

Others: (Unsorted, and seems less important)

Usage in Chatbot and Summarization (again unsorted, and again perhaps less important.....)