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http://www.aclweb.org/anthology/J93-2003
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Identify potential datasets of interest for evaluation on Azure Translation component.
Current datasets gathered:
[WMT (Workshop on Statistical Machine Translation)](https://statmt.org/wmt22/) –…
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**Paper**
Data Augmentation for Low-Resource Neural Machine Translation
**Introduction**
This research focuses on the challenges faced by low-resource languages in the neural machine translation…
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# What's this paper about?
- Introduces **RNN Encoder-Decoder**
- One RNN encodes a sequence into a fixed length vector representation, and the other decodes the representation into another sequence…
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- [ ] A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation: https://www.aclweb.org/anthology/W16-3908.pdf
- [ ] Language Models: https://www.cs.tau.ac.il/~jo…
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See http://www.contrib.andrew.cmu.edu/~apjaffe/smt/decompilation-renaming-2.pdf
Quote from @apjaffe's abstract:
> Decompiled code lacks meaningful variable names. We used statistical machine tra…
ghost updated
6 years ago
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[1] Sequence to Sequence Learning with Neural Networks (http://arxiv.org/abs/1409.3215)
[2] Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation (http://arxiv…
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## Summary
Train, test, evaluate OpenNMT / Moses (traditional) statistical Machine translation model and compare the quality of both outputs.
Training should be performed on a *standardized* train…
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For each connection domain required for the system, describe the distortion and delay that results from the identified connection domains.
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```
这篇paper泛泛地讲了如何用LSTM做序列到序列的学习。
主要思想：
1）用两套LSTM解决翻译中源语言句子和目标语言句子长度不一致的问题。
具体如何训练，详见文章《Learning phrase representations using RNN encoder-decoder for statistical machine translation》。
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