Answers.Body: <p>In this paper: <a href="https://arxiv.org/abs/1711.00043" rel="nofollow noreferrer">Unsupervised Machine Translation Using Monolingual Corpora Only
  </a> the authors proposed a novel method. </p>
  
  <p><a href="https://i.sstatic.net/4lKWv.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/4lKWv.png" alt="enter image description here"></a></p>
  
  <p>Intuitively it is an autoencoder, but the Start Of Sentence token is set to be the language type. </p>
  
  <p>One other advanced method is to use the pre-training model. In this paper: <a href="https://arxiv.org/pdf/1901.07291.pdf" rel="nofollow noreferrer">Cross-lingual Language Model Pretraining</a> researchers proposed an algorithm that utilized the pre-trained multi-lingual trained BERT(with labeled data but we don't need to have a labeled dataset for our task) and the autoencoder mentioned previously. </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-02-29T10:17:08.213Z
Answers.Text: That's crazy! I wonder if it could be a way of addressing the grounding problem too, if  media experiences could somehow be mapped to a shared embedding space . . .
Answers.UserDisplayName: Neil Slater
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-02-29T10:27:13.260Z
Answers.Text: @NeilSlater I know only a little about the "grounding problem" but I thought this paper would be helpful to you: https://arxiv.org/pdf/1609.05518.pdf
Answers.UserDisplayName: Lerner Zhang
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-02-29T09:25:40.197Z
Answers.LastActivityDate: 2020-02-29T09:25:40.197Z
Answers.UserDisplayName: Lerner Zhang
Body: <p>Is it be possible to train a neural network, with no parallel bilingual data, for machine translation?</p>
  
Tags: <machine-learning><unsupervised-learning><machine-translation><unlabeled-datasets>
Title: How to do machine translation with no labeled data?
UserDisplayName: Lerner Zhang
ThreadText: # How to do machine translation with no labeled data?
  
  (Asked by: username_0 on 2020-02-29)
  
  Is it be possible to train a neural network, with no parallel bilingual data, for machine translation?
  
  **Tags:** machine-learning, unsupervised-learning, machine-translation, unlabeled-datasets
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_0 on 2020-02-29. Score: 2
  
  In this paper: [Unsupervised Machine Translation Using Monolingual Corpora Only](https://arxiv.org/abs/1711.00043) the authors proposed a novel method.
  
  [![enter image description here](https://i.sstatic.net/4lKWv.png)](https://i.sstatic.net/4lKWv.png)
  
  Intuitively it is an autoencoder, but the Start Of Sentence token is set to be the language type.
  
  One other advanced method is to use the pre-training model. In this paper: [Cross-lingual Language Model Pretraining](https://arxiv.org/pdf/1901.07291.pdf) researchers proposed an algorithm that utilized the pre-trained multi-lingual trained BERT(with labeled data but we don't need to have a labeled dataset for our task) and the autoencoder mentioned previously.
  
  > **Comments:**
  > **username_1**: That's crazy! I wonder if it could be a way of addressing the grounding problem too, if  media experiences could somehow be mapped to a shared embedding space . . .  
  > **username_0**: @username_1 I know only a little about the "grounding problem" but I thought this paper would be helpful to you: https://arxiv.org/pdf/1609.05518.pdf  
  
  ---
  
  