“NLP Status Report 2017-7-31”版本间的差异

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(process the ancient document)
 
 
(4位用户的16个中间修订版本未显示)
第1行: 第1行:
Until now, Shiji has been split up to 2,5000 pairs of sentence.
+
 
Zizhitongjian has been split up to 2,0000 pairs.
+
{| class="wikitable"
 +
!Date !! People !! Last Week !! This Week
 +
|-
 +
| rowspan="6"|2017/7/31
 +
|Jiyuan Zhang ||
 +
*made the poster for ACL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Acl2017-poster.pdf]
 +
*attempted to fix repeated word, but failed
 +
*done some work of n-gram model of the couplet
 +
||
 +
*generate streame according to a couplet
 +
*complete the task of filling in the blanks of a couplet
 +
 
 +
|-
 +
|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
 +
|-
 +
|Shiyue Zhang ||
 +
 
 +
||
 +
 
 +
|-
 +
|Shipan Ren ||
 +
* looked for the performance(the bleu value) of other models
 +
  on the WMT2014 dataset from the published papers,but not found.
 +
* installed and built Moses on the server 
 +
||
 +
* train statistical machine translation model and test it
 +
  toolkit: Moses
 +
  data sets:WMT2014 en-de、en-fr data sets
 +
* collate experimental results.compare our baseline model with Moses
 +
|-
 +
   
 +
|Jiayu Guo||
 +
*process document.Until now, Shiji has been split up to 2,4000 pairs of sentence.
 +
*Zizhitongjian has been split up to 1,6000 pairs.
 +
||
 +
*adjust jieba source code, in order to make jieba more accurate for ancient language wordpiece
 +
*read model source code
 +
|-
 +
|}

2017年8月21日 (一) 00:51的最后版本

Date People Last Week This Week
2017/7/31 Jiyuan Zhang
  • made the poster for ACL [1]
  • attempted to fix repeated word, but failed
  • done some work of n-gram model of the couplet
  • generate streame according to a couplet
  • complete the task of filling in the blanks of a couplet
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
Shiyue Zhang
Shipan Ren
  • looked for the performance(the bleu value) of other models
 on the WMT2014 dataset from the published papers,but not found.
  • installed and built Moses on the server
  • train statistical machine translation model and test it
 toolkit: Moses
 data sets:WMT2014 en-de、en-fr data sets
  • collate experimental results.compare our baseline model with Moses
Jiayu Guo
  • process document.Until now, Shiji has been split up to 2,4000 pairs of sentence.
  • Zizhitongjian has been split up to 1,6000 pairs.
  • adjust jieba source code, in order to make jieba more accurate for ancient language wordpiece
  • read model source code