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第14行: |
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| |Aodong LI || | | |Aodong LI || |
− | | + | * Got 55,000+ Englsih poems and 260,000+ lines after preprocessing |
| + | * Added phase separators as the style indicator, and every line has at least one separator |
| + | * Training loss didn't decrease very much, only from 440 to 50 |
| + | * The translation quality deteriorated when added language model |
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− | | + | * Try to use a larger language model to decrease the training loss |
| + | * Try to use character-based MT in English-Chinese translation |
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| |Shiyue Zhang || | | |Shiyue Zhang || |
Date |
People |
Last Week |
This Week
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2017/7/3
|
Jiyuan Zhang |
- made the poster for ACL
- attempted to fix repeated word, but failed
- done some work of n-gram model of the couplet
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- generate streame according to a couplet
- complete the task of filling in the blanks of a couplet
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Aodong LI |
- Got 55,000+ Englsih poems and 260,000+ lines after preprocessing
- Added phase separators as the style indicator, and every line has at least one separator
- Training loss didn't decrease very much, only from 440 to 50
- The translation quality deteriorated when added language model
|
- Try to use a larger language model to decrease the training loss
- Try to use character-based MT in English-Chinese translation
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Shiyue Zhang |
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Shipan Ren |
- trained two models of the baseline using WMT2014 en-fr datasets
under training
- read some papers(memory-augmented-nmt and Memory augmented Chinese-Uyghur Neural Machine Translation)
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- read memory-augmented-nmt code
- read papers about memory augmented NMT
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Jiayu Guo |
- process document.
- Shiji has been split up to 2,5000 pairs of sentence.
- Zizhitongjian has been split up to 2,0000 pairs.
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