“2020-07-27”版本间的差异

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（以“{| class="wikitable" !People !! This Week !! Next Week !! Task Tracking (<font color="red">DeadLine</font>) |- |- |Dong Wang || * || * || * |- |- |Yunqi Cai...”为内容创建页面）
 
 
（8位用户的9个中间修订版本未显示）
第6行： 第6行：
 
|Dong Wang
 
|Dong Wang
 
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* More investigation on Maximum Gaussianlity training
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* Reformulate the TASLP paper
 
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*  
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* Complete the MG paper
 +
* Start working on the condition transfer (CT) paper
 
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*   
第17行： 第19行：
 
|Yunqi Cai
 
|Yunqi Cai
 
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*experiments on Gaussian regularization
 
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第28行： 第30行：
 
|Zhiyuan Tang
 
|Zhiyuan Tang
 
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* Adaptation with nf-dt asr.
 
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*  
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* Continue.
 
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第39行： 第41行：
 
|Lantian Li
 
|Lantian Li
 
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* Compare two MLE methods.
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* Length norm and whitening in NL scoring.
 
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*  
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* Self-learning plus NDA.
 
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第50行： 第53行：
 
|Ying Shi
 
|Ying Shi
 
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* sub space with trainable mean of r code
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* sub space flow with gauss. mixture r code
 
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*
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* analysis the gaussianlity of r space
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* verify the robustness of sub space flow
 
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第62行： 第66行：
 
|Haoran Sun
 
|Haoran Sun
 
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* Analysed latent space of ML-DNF
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* Classification via logpz
 
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* Analysises of subspace DNF
 
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第84行： 第89行：
 
|Jiawen Kang
 
|Jiawen Kang
 
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* Read NDA papers;
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* MAML code;
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* MAML experiments.
 
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*  
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* MAML SSMC&MC experiments.
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*
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第97行： 第102行：
 
|Ruiqi Liu
 
|Ruiqi Liu
 
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*
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* revise the paper draft.
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* Multi-genre generalization.
 +
* MC experiments data.
 
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−
*
+
* MC experiments
 
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第107行： 第114行：
 
|Haolin Chen
 
|Haolin Chen
 
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*  
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* Subspace Flow
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** Noisy r var=1, fixed mean
 +
** GMM Loss
 
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−
*  
+
* Subspace Flow
 +
** Other noise
 +
** Improve performance
 
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*   
 
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2020年7月27日 (一) 00:01的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • More investigation on Maximum Gaussianlity training
  • Reformulate the TASLP paper
  • Complete the MG paper
  • Start working on the condition transfer (CT) paper
Yunqi Cai
  • experiments on Gaussian regularization
Zhiyuan Tang
  • Adaptation with nf-dt asr.
  • Continue.
Lantian Li
  • Compare two MLE methods.
  • Length norm and whitening in NL scoring.
  • Self-learning plus NDA.
Ying Shi
  • sub space with trainable mean of r code
  • sub space flow with gauss. mixture r code
  • analysis the gaussianlity of r space
  • verify the robustness of sub space flow
Haoran Sun
  • Analysed latent space of ML-DNF
  • Classification via logpz
  • Analysises of subspace DNF
Yue Fan
Jiawen Kang
  • Read NDA papers;
  • MAML code;
  • MAML experiments.
  • MAML SSMC&MC experiments.
Ruiqi Liu
  • revise the paper draft.
  • Multi-genre generalization.
  • MC experiments data.
  • MC experiments
Haolin Chen
  • Subspace Flow
    • Noisy r var=1, fixed mean
    • GMM Loss
  • Subspace Flow
    • Other noise
    • Improve performance
取自“http://index.cslt.org/mediawiki/index.php?title=2020-07-27&oldid=35303”